Conference Program
PROGRAM
Conference Program
  • Conference Program
  • Keynote Speakers
  • Accepted Papers
  • Poster Session
  • Tutorials
  • Workshops
  • CIKM2025 AnalytiCup
Monday, November 10, 2025
Tutorials, Industry Day, PhD Symposium
   
Nov10 Room
205A		 Room
205B		 Room
201		 Room
202		 Room
203		 Room
209A		 Room
209B

08:00

 Breakfast
Registration opens at 8:00 AM (2F Lobby)

08:45

     INDUSTRY DAY:
Welcome and Introduction		        
09:00 TUTORIAL:
Retrieval of Graph Structured Objects: Theory and Applications		 TUTORIAL:
Neural Differential Equations for Continuous-Time Analysis		 INDUSTRY DAY 1:
Infrastructure and Emerging Applications		 TUTORIAL:
Fairness in Language Models: A Tutorial		 TUTORIAL:
Generative Models for Synthetic Data: Transforming Data Mining in the GenAI Era		 TUTORIAL:
Uncertain Boundaries: A Tutorial on Copyright Challenges and Cross-Disciplinary Solutions for Generative AI		 PhD
Symposium
Presentation Session 1
10:30 Coffee break (2F Lobby)
11:00 TUTORIAL:
Retrieval of Graph Structured Objects: Theory and Applications		 TUTORIAL:
Neural Differential Equations for Continuous-Time Analysis 		INDUSTRY DAY 2:
Recommendation and Retrieval Systems		 TUTORIAL:
Fairness in Language Models: A Tutorial		 TUTORIAL:
Generative Models for Synthetic Data: Transforming Data Mining in the GenAI Era		 TUTORIAL:
Uncertain Boundaries: A Tutorial on Copyright Challenges and Cross-Disciplinary Solutions for Generative AI		 PhD
Symposium
Presentation Session 2
12:45 Lunch break
13:45 TUTORIAL:
A Tutorial on Hypergraph Neural Networks: An In-Depth and Step-By-Step Guide		 TUTORIAL:
Socially Responsible and Trustworthy Generative Foundation Models: Principles, Challenges, and Practices		 INDUSTRY DAY 3:
Trust and Safety AI		 TUTORIAL:
Continual Recommender Systems		 TUTORIAL:
Towards Large Generative Recommendation: A Tokenization Perspective		 TUTORIAL:
Neural Shifts in Collaborative Team Recommendation		 PhD
Symposium
Presentation Session 3
15:30 Coffee break (2F Lobby)
16:00 TUTORIAL:
A Tutorial on Hypergraph Neural Networks: An In-Depth and Step-By-Step Guide		 TUTORIAL:
 Socially Responsible and Trustworthy Generative Foundation Models: Principles, Challenges, and Practices		 INDUSTRY DAY 4:
LLM Applications in E-commerce and Ads		 TUTORIAL:
Continual Recommender Systems		 TUTORIAL:
Towards Large Generative Recommendation: A Tokenization Perspective		 TUTORIAL:
Neural Shifts in Collaborative Team Recommendation		 PhD
Symposium
Presentation Session 4
17:30 INDUSTRY DAY:
Closing
Tuesday, November 11, 2025
Main Conference
FP: Full Research Paper Track
ARS: Applied Research Paper Track
Nov 11 Room
205A		 Room
205B		 Room
206		 Room
201		 Room
202		 Room
203		 Room
210		 Room
209A		 Room
209B

07:30

 Breakfast
Registration opens at 8:00 AM (3F Lobby)

08:30

 Conference Opening
(Auditorium, 3F)

09:00

 KEYNOTE 1:
Numerical Linear Algebraic Foundations for Large-Scale Unsupervised Learning (Haesun Park, Georgia Institute of Technology)
Room: Auditorium, 3F

10:30

 Coffee break (3F Lobby)

11:00

 FP1:
Anomaly Detection		 FP2:
Recommender Systems 1		 FP3:
Graph Learning 1		 FP4:
Machine Learning & AI 1		 FP5:
LLMs 1		 FP6:
Databases		 FP7:
Computer Vision		 ARS1:
Spatial Learning and Intelligence		 ARS2:
User Modeling and Engagement Prediction

12:45

 Lunch break
(Box lunch served in the 2F Lobby for 3-day/5-day registrants)

13:45

 FP8:
Fairness 1		 FP9:
Recommender Systems 2		 FP10:
Graph Learning 2		 FP11:
Machine Learning & AI 2		 FP12:
LLMs 2		 FP13:
Data Mining 1		 FP14:
Content Understanding		 ARS3:
Forecasting and Operational Optimization		 ARS4:
Research, Retrieval and Ranking in Online Platforms

15:30

 Coffee break (3F Lobby)

16:00

 FP15:
Fairness 2		 FP16:
Recommender Systems 3		 FP17:
Graph Learning 3		 FP18:
Machine Learning & AI 3		 FP19:
LLMs 3		 FP20:
Data Mining 2 		FP21:
Multimodality		   Backup1 ARS5:
Optimization for Ads and Promotions in E-commerce

17:45 ~ 
19:30

 Welcome Reception and Poster (short papers, resource papers) and Demo session
Room E, 3F
Wednesday, November 12, 2025
Main Conference
FP: Full Research Paper Track
ARS: Applied Research Paper Track
Nov 12 Room
205A		 Room
205B		 Room
206		 Room
201		 Room
202		 Room
203		 Room
210		 Room
209A		 Room
209B
08:00 Breakfast
Registration opens at 8:00 AM (3F Lobby)
09:00 KEYNOTE 2:
AI Planning for Data Exploration (Sihem Amer-Yahia, CNRS / Univ. Grenoble Alpes)
Room: Auditorium, 3F
10:30 Coffee break (3F Lobby)
11:00 FP22:
Explainability		 FP23
Recommender Systems 4		 FP24:
Knowledge Graphs 1		 FP25:
Machine Learning & AI 4		 FP26:
Reinforce-
ment Learning		 FP27:
Data Quality		 FP28:
Time Series Data 1		 ARS6:
Finance,
Market and Risk Analytics		 ARS7:
Graph Learning and Relational Modeling
12:45 Lunch break
13:45 FP29:
Privacy & Security 1		 FP30:
Personalization 1		 FP31:
Graph Data Mining 1		 FP32:
Transfer Learning 1		 FP33:
LLM & RecSys 1		 FP34:
Evaluation & Benchmark		 FP35:
Time Series Data 2		 ARS8:
LLMs for Reasoning and Information Retrieval		 ARS9:
Representation Learning and Cold-Start Solutions
15:30 Coffee break (3F Lobby)
16:00 ~
17:45		 FP36:
Privacy & Security 2		 FP37:
Personalization 2		 FP38:
Graph Data Mining 2		 FP39:
Transfer Learning 2		 FP40:
LLM & RecSys 2		 FP41:
Performance		 FP42:
Time Series Data 3		 ARS10:
Generative and Retrieval-
Enhanced Recommen-
dation		 ARS11:
Advances
in Industrial-
Scale Recommen-
dation
18:30 ~
22:00		 Banquet (Grand Ballroom, 1F)
Thursday, November 13, 2025
Main Conference
FP: Full Research Paper Track
ARS: Applied Research Paper Track
Nov 13 Room
205A		 Room
205B		 Room
206		 Room
201		 Room
202		 Room
203		 Room
210		 Room
209A		 Room
209B
08:00 Breakfast
Registration opens at 8:00 AM (3F Lobby)
09:00 KEYNOTE 3:
The Geometry of Knowledge and Computational Discovery (Yong-Yeol Ahn, University of Virginia)
Room: Auditorium, 3F
10:30 Coffee break (3F Lobby)
11:00 FP43:
Robust & Resilient AI		 FP44:
Graph-based Recommen-
dation		 FP45:
Knowledge Graphs 2		 FP46:
Natural Language Processing		 FP47:
LLM & IR		 FP48:
AI for Science		 FP49:
Spatio-
Temporal Data 1		 FP50:
Social Networks 1		 ARS12:
Multimodal Interaction and Human-
Centered AI
12:45 Lunch break
(Box lunch served in the 2F Lobby for 3-day/5-day registrants)
Business Meeting (Room 201, 2F)
13:45 FP51:
Federated Learning 1		 FP52:
Sequential Recommen-
dation		 FP53:
Graph Neural Networks 1		 FP54:
Question Answering		 FP55:
LLM & KG		 FP56:
Search & Retrieval 1		 FP57:
Spatio-
Temporal Data 2		 FP58:
Social Networks 2		 ARS13:
Multi-Modal and Personalized User Modeling
15:30 Coffee break (3F Lobby)
16:00 FP59:
Federated Learning 2		 FP60:
Biomedicine & Health		 FP61:
Graph Neural Networks 2		 FP62:
Conversational Interactions		 FP63:
LLM & Time Series		 FP64:
Search & Retrieval 2		 FP65:
Urban Systems		   Backup2 ARS14:
LLM/MLLM and Generative AI Applications
Friday, November 14, 2025
Workshops, AnalytiCup
Nov 14 Room
205A		 Room
205B		 Room
206		 Room
201		 Room
202		 Room
203		 Room
210		 Room
209A		 Room
209B
08:00 Breakfast
Registration opens at 8:00 AM (2F Lobby)
09:00 WORKSHOP: Advances in Financial AI: Innovations, Risk, and Responsibility in the Era of LLMs WORKSHOP: Proactive Conversational Information Seeking with Large Language Models (ProActLLM) WORKSHOP:
The 2nd International Workshop on Decentralized Search and Recommen-
dation(DESERE 2025)		 WORKSHOP:
Multimodal Generative Search and Recommen-
dation		 WORKSHOP:
Trustworthy Knowledge Discovery and Data Mining (TrustKDD)		 WORKSHOP:
The 1st Workshop on LLM Agents for Social Simulation (LASS)		 ANALYTICUP:
FinVolution Deepfake Face Detection Challenge		 WORKSHOP:
Frontiers in Graph Machine Learning for the Large Model Era		 WORKSHOP:
Spatio-Temporal Data Intelligence and Foundation Models (STIntelligence)
10:30 Coffee break (2F Lobby)
11:00 WORKSHOP: Advances in Financial AI: Innovations, Risk, and Responsibility in the Era of LLMs WORKSHOP: Proactive Conversational Information Seeking with Large Language Models (ProActLLM) WORKSHOP:
The 2nd International Workshop on Decentralized Search and Recommen-
dation (DESERE 2025)		 WORKSHOP:
Multimodal Generative Search and Recommen-
dation		 WORKSHOP:
Trustworthy Knowledge Discovery and Data Mining (TrustKDD)		 WORKSHOP:
The 1st Workshop on LLM Agents for Social Simulation (LASS)		 ANALYTICUP:
FinVolution Deepfake Face Detection Challenge		 WORKSHOP:
Frontiers in Graph Machine Learning for the Large Model Era		 WORKSHOP:
Spatio-Temporal Data Intelligence and Foundation Models (STIntelligence)
12:45 Lunch break
13:45 WORKSHOP: Advances in Financial AI: Innovations, Risk, and Responsibility in the Era of LLMs WORKSHOP: Proactive Conversational Information Seeking with Large Language Models (ProActLLM) WORKSHOP:
The 6th Workshop on Secure IoT, Edge and Cloud systems (SIoTEC 2025)		 WORKSHOP:
The 1st Workshop on Small and Efficient Large Language Models for Knowledge Extraction (SmaLLEXT)		 WORKSHOP:
Recommender Systems for Sustainable Development (RS4SD)		 WORKSHOP:
Human-Centric AI: From Explainability and Trustworthiness to Actionable Ethics		 ANALYTICUP:
Alibaba International E-commerce Product Search Competition		 WORKSHOP:
The 1st International Workshop on Retrieval-Driven Generative AI & ScienceON AI Challenge 2025		 WORKSHOP:
Advances in Medical Knowledge Systems: LLMs, RAG and Foundation Models
15:30 Coffee break (2F Lobby)
16:00 ~ 17:30 WORKSHOP: Advances in Financial AI: Innovations, Risk, and Responsibility in the Era of LLMs WORKSHOP: Proactive Conversational Information Seeking with Large Language Models (ProActLLM) WORKSHOP:
The 6th Workshop on Secure IoT, Edge and Cloud systems (SIoTEC 2025)		 WORKSHOP:
The 1st Workshop on Small and Efficient Large Language Models for Knowledge Extraction (SmaLLEXT)		 WORKSHOP:
Recommender Systems for Sustainable Development (RS4SD)		 WORKSHOP:
Human-Centric AI: From Explainability and Trustworthiness to Actionable Ethics		 ANALYTICUP:
Alibaba International E-commerce Product Search Competition		 WORKSHOP:
The 1st International Workshop on Retrieval-Driven Generative AI & ScienceON AI Challenge 2025		 WORKSHOP:
Advances in Medical Knowledge Systems: LLMs, RAG and Foundation Models
FP Sessions
FP1: Anomaly Detection
Correlation-aware Online Change Point Detection (Chengyuan Deng, Zhengzhang Chen, Xujiang Zhao, Haoyu Wang, Junxiang Wang, Jie Gao and Haifeng Chen)
FreeGAD: A Training-Free yet Effective Approach for Graph Anomaly Detection (Yunfeng Zhao, Yixin Liu, Shiyuan Li, Qingfeng Chen, Yu Zheng and Shirui Pan)
Self-supervised Dual-view Framework with Tailored Negative Sampling for New Activity Detection (Hyunju Kim and Dongman Lee)
DDE-CLIP: Detail-Guided Dual-Modal Enhancement for Zero-Shot Anomaly Detection (Zehao Deng, Qingzhi Ma and An Liu)
MetaCAN: Improving Generalizability of Few-shot Anomaly Detection with Meta-learning (Zhisheng Lv, Jianfeng Zhang, Songlei Jian, Chenlin Huang, Hongguang Zhang, Guansong Pang and Zhong Liu)
Fast Outlier Detection in Oblique Subspaces (Bowen Li, Charu Aggarwal and Peixiang Zhao)
Addressing the Distortion of Community Representations in Anomaly Detection on Attributed Networks (Enbo He, Yitong Hao, Yue Zhang, Guisheng Yin and Lina Yao)
FP2: Recommender Systems 1
Frequency-Decoupled Distillation for Efficient Multimodal Recommendation (Ziyi Zhuang, Hongji Li, Junchen Fu, Jiacheng Liu, Joemon Jose, Youhua Li and Yongxin Ni)
Local Structure-Adaptive Graph Filtering for Collaborative Filtering (Yijun Sheng, Ximing Chen, Yanyan Liu, Pui Ieng Lei and Zhiguo Gong)
A Node-Aware Dynamic Quantization Approach for Graph Collaborative Filtering (Lin Li, Chunyang Li, Yu Yin, Xiaohui Tao and Jianwei Zhang)
Federated Continual Recommendation (Jaehyung Lim, Wonbin Kweon, Woojoo Kim, Junyoung Kim, Seongjin Choi, Dongha Kim and Hwanjo Yu)
Benefit from Rich: Tackling Search Interaction Sparsity in Search Enhanced Recommendation (Teng Shi, Weijie Yu, Xiao Zhang, Ming He, Jianping Fan and Jun Xu)
Twin-Flow Generative Ranking Network for Recommendation (Hao Guo, Erpeng Xue, Lei Huang, Shichao Wang, Xiaolei Wang, Lei Wang, Jinpeng Wang, Zeshun Li and Sheng Chen)
A Self-Supervised Mixture-of-Experts Framework for Multi-behavior Recommendation (Kyungho Kim, Sunwoo Kim, Geon Lee and Kijung Shin)
FP3: Graph Learning 1
Contrastive Multi-view Graph Hashing (Yang Xu, Zuliang Yang and Kaiming Ting)
ConGM: Contrastive Graph Matching for Graph Self-Supervised Learning (Hongxiang Lin, Lei Wang, Huiying Hu and Xiaoqing Lyu)
GCLS$^2$: Towards Efficient Community Detection Using Graph Contrastive Learning with Structure Semantics (Qi Wen, Yiyang Zhang, Yutong Ye, Yingbo Zhou, Nan Zhang, Xiang Lian and Mingsong Chen)
Learning Global-Local Multi-Scale Node Embeddings with Random Walks and Landmark-Guided Optimization (Ali Assi, Karabadji Nour Elislem, Mohamed Elati and Wajdi Dhifli)
SGPT: Few-Shot Prompt Tuning for Signed Graphs (Zian Zhai, Sima Qing, Xiaoyang Wang and Wenjie Zhang)
DiRW: Path-Aware Digraph Learning for Heterophily (Daohan Su, Xunkai Li, Zhenjun Li, Yinping Liao, Rong-Hua Li and Guoren Wang)
Leveraging Multi-facet Paths for Heterogeneous Graph Representation Learning (Jongwoo Kim, Chu Seongyeub, Hyungmin Park, Bryan Wong, Kijun Han and Mun Yi)
FP4: Machine Learning & AI 1
Model-Agonistic Iterative Graph Diversification for Improving Learning to Solve Graph Optimization Problems (Bay-Yuan Hsu, Chia-Hsun Lu and Chih-Ya Shen)
Oblivious Johnson--Lindenstrauss embeddings for compressed Tucker decompositions (Matthew Pietrosanu, Bei Jiang and Linglong Kong)
SpeedSteiner: A Fast O(k^{1/2})-Approximation Algorithm for Directed Steiner Tree (Guangyi Zhang, Nikolaj Tatti and Aristides Gionis)
ConsensNet: A Unified Consensus-Centric Framework for Incomplete Multi-View Clustering (Yifei Chen, Xiaolin Xiao and Yue-Jiao Gong)
Tight Bounds for Jensen’s Gap with Applications to Variational Inference (Marcin Mazur, Tadeusz Dziarmaga, Piotr Kościelniak and Łukasz Struski)
From Policy Comparison to Process Consistency and Beyond (Yifan Xu, Yujia Yin, Yiming Xing and Yifan Chen)
Beyond Return Conditioning: Multi-scale Sequence Modeling and Advantage-Guided Policy Routing for Offline RL (Kunbao Wu, Xinning Zhu, Yang Qin, Tieru Wang, Jianzhou Diao and Zheng Hu)
FP5: LLMs 1
Yes is Harder than No: A Behavioral Study of Framing Effects in Large Language Models Across Downstream Tasks (Ziheng Zhang, Weixin Zeng, Jiuyang Tang, Ji Wang and Xiang Zhao)
Hyperbolic Prompt Learning for Incremental Event Detection with LLMs (Xiujin Zhang, Wenxin Jin, Haotian Hong, Pengfei Zhang, Jiting Li, Kongjing Gu, Hao Peng and Li Sun)
A Cost-aware Approach for Collaborating Large Language Models and Small Language Models (Zheng Li, Xuyun Zhang, Sheng Lu, Hua Deng, Hao Tian and Wanchun Dou)
Unplug and Play Language Models: Decomposing Experts in Language Models at Inference Time (Nakyeong Yang, Jiwon Moon, Junseok Kim, Yunah Jang and Kyomin Jung)
CEM: A Data-Efficient Method for Large Language Models to Continue Evolving From Mistakes (Haokun Zhao, Jinyi Han, Jie Shi, Chengyu Du, Jiaqing Liang, Yanghua Xiao, Weikang Zhou, Zeye Sun and Fei Yu)
SyLeR: A Framework for Explicit Syllogistic Legal Reasoning in Large Language Models (Kepu Zhang, Weijie Yu, Zhongxiang Sun and Jun Xu)
Adapting Large Language Models to Log Analysis with Interpretable Domain Knowledge (Yuhe Ji, Yilun Liu, Feiyu Yao, Minggui He, Shimin Tao, Xiaofeng Zhao, Chang Su, Xinhua Yang, Weibin Meng, Yuming Xie, Boxing Chen, Shenglin Zhang and Yongqian Sun)
FP6: Databases
General Adaptive Memory Allocation for Learned Bloom Filters (You Shang, Xiang He, Ruiyuan Li, Yingying Sun, Guanyao Li, Guangchao Yang, Junbo Zhang and Yu Zheng)
TKHist: Cardinality Estimation for Join Queries via Histograms with Dominant Attribute Correlation Finding (Renrui Li, Qingzhi Ma, Jiajie Xu, Lei Zhao and An Liu)
Federated Approximate Query Processing Based on Deep Models (Yutong Xie, Qingzhi Ma, Lei Zhao and An Liu)
A Privacy-preserving Spatial Dataset Joinable Search in Cloud (Zhengkai Zhang, Hua Dai, Hao Zhou, Mingfeng Jiang, Pengyue Li and Geng Yang)
InstANNS: Scalable Approximate Nearest Neighbor Search via Cost-Efficient In-Storage Processing (Bonggeun Sim, Yushin Kim, Minseo Kim, Yeonhong Park and Jae W. Lee)
StreamingRT: Stream KNN Join with Ray Tracing Core (Shixi Yang, Kai Zhang, Zhigang Zhao, Chunxiao Wang, Zhenying He, Yinan Jing and X. Sean Wang)
CCAgent: Coordinating Collaborative Data Scaling for Operating System Agents via Web3 (Liang Chen, Haozhe Zhao, Yinzhen Huang, Yang Luo, Tsekai Lin, Weichu Xie, Ruoyu Wu, Peiyi Wang, Runxin Xu, Ming Wu and Baobao Chang)
FP7: Computer Vision
Point-DMAE: Point Cloud Self-supervised Learning via Density-directed Masked Autoencoders (Xianglong Jin, Zheng Wang, Wenjie Zheng and Feiping Nie)
BOVIS: Bias-Mitigated Object-Enhanced Visual Emotion Analysis (Yubeen Lee, Sangeun Lee, Junyeop Cha, Jufeng Yang and Eunil Park)
KIEPrompter: Leveraging Lightweight Models' Predictions for Cost-Effective Key Information Extraction using Vision LLMs (Lorenzo Vaiani, Yihao Ding, Luca Cagliero, Jean Lee, Paolo Garza, Josiah Poon and Caren Han)
SupLID: Geometrical Guidance for Out-of-Distribution Detection in Semantic Segmentation (Nimeshika Udayangani Hewa Dehigahawattage, Sarah Erfani and Christopher Leckie)
Calibrating on Medical Segmentation Model through Signed Distance (Wenhao Liang, Wei Emma Zhang, Lin Yue, Miao Xu, Olaf Maennel and Weitong Chen)
AdaHet-MKD: An Adaptive Heterogeneous Multi-teacher Knowledge Distillation for Medical Image Analysis (Helin Wang, Wei Du, Ning Liu, Qian Li, Yanyu Xu and Lizhen Cui)
MFAE: Multimodal Feature Adaptive Enhancement for Fake News Video Detection (Wenhao Wang, Mingxin Li, Jiao Qiao, Haotong Du, Xianghua Li, Chao Gao and Zhen Wang)
FP8: Fairness 1
Calibrated and Diverse News Coverage (Tianyi Zhou, Stefan Neumann, Kiran Garimella and Aristides Gionis)
Improving Recommendation Fairness via Graph Structure and Representation Augmentation (Tongxin Xu, Wenqiang Liu, Chenzhong Bin, Cihan Xiao, Zhixin Zeng and Tianlong Gu)
Exploring the Tradeoff Between Diversity and Discrimination for Continuous Category Discovery (Ruobing Jiang, Yang Liu, Haobing Liu, Yanwei Yu and Chunyang Wang)
When Variety Seeking Meets Multi-Sided Recommendation Fairness: A Consistent and Personalized Multi-Objective Optimization Framework (Jiayi Guo, Jiangning He, Chenyan Wang and Xinran Wu)
Selective Mixup for Debiasing Question Selection in Computerized Adaptive Testing (Mi Tian, Kun Zhang, Fei Liu, Jinglong Li, Yuxin Liao, Chenxi Bai, Zhengtao Tan, Le Wu and Richang Hong)
LeadFairRec: LLM-enhanced Discriminative Counterfactual Debiasing for Two-sided Fairness in Recommendation (Yimin Hou, Yue Kou, Derong Shen, Xiangmin Zhou, Dong Li, Tiezheng Nie and Ge Yu)
Evaluating and Addressing Fairness Across User Groups in Negative Sampling for Recommender Systems (Yueqing Xuan, Kacper Sokol, Mark Sanderson and Jeffrey Chan)
FP9: Recommender Systems 2
MI4Rec: Pretrained Language Model based Cold-Start Recommendation with Meta-Item Embeddings (Zaiyi Zheng, Yaochen Zhu, Haochen Liu, Mingxuan Ju, Tong Zhao, Neil Shah and Jundong Li)
NR-GCF: Graph Collaborative Filtering with Improved Noise Resistance (Yijun Chen, Bohan Li, Yicong Li, Lixiang Song, Haofen Wang, Wenlong Wu, Junnan Zhuo and Hongzhi Yin)
Enhancing Dual-Target Cross-Domain Recommendation via Similar User Bridging (Qi Zhou, Xi Chen, Chuyu Fang, Jianji Wang, Chuan Qin and Fuzhen Zhuang)
What Data is Really Necessary? A Feasibility Study of Inference Data Minimization for Recommender Systems (Jens Leysen, Marco Favier and Bart Goethals)
Hierarchical Multi-View Contrastive Learning for Bundle Recommendation (Shiqin Liu, Chaozhuo Li, Minjun Zhao, Litian Zhang and Jiajun Bu)
Hypercomplex Prompt-aware Multimodal Recommendation (Zheyu Chen, Jinfeng Xu, Hewei Wang, Shuo Yang, Zitong Wan and Haibo Hu)
Mitigating Latent Confounding Bias in Recommender Systems (Jianfeng Deng, Qingfeng Chen, Debo Cheng, Xiaojing Du, Jiuyong Li and Lin Liu)
FP10: Graph Learning 2
Adaptive Heterogeneous Graph Neural Networks: Bridging Heterophily and Heterogeneity (Qin Chen and Guojie Song)
Data-centric Prompt Tuning for Dynamic Graphs (Yufei Peng, Cheng Yang, Zhengjie Fan and Chuan Shi)
Learning from Graph: Mitigating Label Noise on Graph through Topological Feature Reconstruction (Zhonghao Wang, Yuanchen Bei, Sheng Zhou, Zhiyao Zhou, Jiapei Fan, Hui Xue, Haishuai Wang and Jiajun Bu)
AMBER: Adaptive Meta Balanced Paradigm for Heterogeneous Graph-Based Knowledge Tracing (Lifan Sun, Zichen Yuan, Ersheng Ni, Weihua Cheng, Xinyuan Song, Linkun Dai, Hongwei Jiang, Sibo Xu, Mengmeng Chen, Yucen Zhuang, Yongxin Ni and Youhua Li)
GraphRCG: Self-Conditioned Graph Generation (Song Wang, Zhen Tan, Xinyu Zhao, Tianlong Chen, Huan Liu and Jundong Li)
Learning Graph Edit Distance via Node Matching Patterns (Junkyu Lee and Jongik Kim)
Disentangling Complex Questions in LLMs via Multi-Hop Dependency Graphs (Roland Oruche, Alphaeus Dmonte, Vani Seth, Zian Zeng, Yuanxun Zhang, Marcos Zampieri and Prasad Calyam)
FP11: Machine Learning & AI 2
Adaptive Spline Networks in the Kolmogorov–Arnold Framework: Knot Analysis and Stability Enhancement (Liangwei Zheng, Wei Emma Zhang, Lin Yue, Miao Xu, Olaf Maennel and Weitong Chen)
Learning conditional probability distributions for robust probabilistic inference in Bayesian network (Xinran Wu, Kun Yue, Huashuai Liu and Liang Duan)
Force Matching with Relativistic Constraints: A Physics-Inspired Approach to Stable and Efficient Generative Modeling (Yang Cao, Bo Chen, Xiaoyu Li, Yingyu Liang, Zhizhou Sha, Zhenmei Shi, Zhao Song and Mingda Wan)
Latent Variable Modeling for Robust Causal Effect Estimation (Tetsuro Morimura, Tatsushi Oka, Yugo Suzuki and Daisuke Moriwaki)
Multi-Armed Bandits with Biased and Heteroscedastic Auxiliary Rewards (Zechen Yin and Zhixuan Fang)
Quantized Factor Identifiable Causal Effect Variational Autoencoder (Sujeong Song, Junghyo Sohn, Eunsong Kang and Heung-Il Suk)
GFlowNet with Gradient-based Optimization for Bayesian Network Structure Learning (Zhu Yang, Kun Yue, Qi Zhiwei, Liang Duan and Jianyu Li)
FP12: LLMs 2
Rethinking the Training Paradigm of Discrete Token-Based Multimodal LLMs: An Analysis of Text-Centric Bias (Wansik Jo, Jooyeong Na, Soyeon Hong, Seungtaek Choi and Hyunsouk Cho)
Unlocking the Potential of Smaller Language Models as Superior Instruction Evolvers (Tingfeng Hui, Lulu Zhao, Guanting Dong, Yaqi Zhang and Sen Su)
LLM4CD: Leveraging Large Language Models for Open-World Knowledge Augmented Cognitive Diagnosis (Weiming Zhang, Lingyue Fu, Qingyao Li, Kounianhua Du, Jianghao Lin, Jingwei Yu, Wei Xia, Weinan Zhang, Ruiming Tang and Yong Yu)
Enhancing and Assessing Instruction-Following with Fine-Grained Instruction Variants (Jiuding Yang, Hui Liu, Weidong Guo, Yu Xu and Di Niu)
Constraint Back-translation Improves Complex Instruction Following of Large Language Models (Yunjia Qi, Hao Peng, Xiaozhi Wang, Bin Xu, Lei Hou and Juanzi Li)
Multi-Turn Interactions for Text-to-SQL with Large Language Models (Guanming Xiong, Junwei Bao, Hongfei Jiang, Yang Song and Wen Zhao)
Evaluating Robustness of LLMs in Question Answering on Multilingual Noisy OCR Data (Bhawna Piryani, Jamshid Mozafari, Abdelrahman Abdallah, Antoine Doucet and Adam Jatowt)
FP13: Data Mining 1
Subclass-Aware Inclusive Classifier via Repulsive Hidden Strata (Namita Bajpai, Jiaul H Paik and Sudeshna Sarkar)
A Robust and High-Efficiency Active Clustering Framework with Multi-User Collaboration (Wen-Bo Xie, Tian Zou, Tao Deng, Xuan-Lin Zhu, Xun Fu, Qiu-Yu Wang, Bin Chen and Xin Wang)
Revisiting Long-Tailed Learning: Insights from an Architectural Perspective (Yuhan Pan, Yanan Sun and Wei Gong)
OBDD-NET: End-to-End Learning of Ordered Binary Decision Diagrams (Junming Qiu, Rongzhen Ye, Weilin Luo, Kunxun Qi, Hai Wan and Yue Yu)
FunLoc: A Novel Function-level Bug Localization Framework Enhanced by Contrastive and Active Learning Strategies (Ziye Zhu, Liangliang Peng, Yu Wang, Yun Li and Long Xianzhong)
Proto-Yield: An Uncertainty-Aware Prototype Network for Yield Prediction in Real-world Chemical Reactions (Kehan Guo, Zhen Liu, Zhichun Guo, Bozhao Nan, Olexandr Isayev, Nitesh Chawla, Olaf Wiest and Xiangliang Zhang)
Dynamic Ensemble Member Selection for Data Stream Classification (Yibin Sun, Bernhard Pfahringer, Heitor Murilo Gomes and Albert Bifet)
FP14: Content Understanding
PERC: A Prior-Guided Framework for Classifying Long-Content Educational Resources with Imbalanced Category Distributions (Quanlong Guan, Xiuliang Duan, Zhi Chen, Xingyu Zhu, Jianbo Huang, Xinzhong Liu, Zonglin Liu and Liangda Fang)
Research on Event Extraction Method Based on Multi-grained Fusion and Scene Graph Enhancement (Xiaoyu Wang, Tao Sun, Gengchen Liu, Zhi Yang, Jiahui Liu and Zimeng Xu)
As Good as It KAN Get: High-Fidelity Audio Representation (Patryk Marszałek, Maciej Rut, Piotr Kawa, Przemysław Spurek and Piotr Syga)
Efficient Multimodal Streaming Recommendation via Expandable Side Mixture-of-Experts (Yunke Qu, Liang Qu, Tong Chen, Quoc Viet Hung Nguyen and Hongzhi Yin)
ParaStyleTTS: Toward Efficient and Robust Paralinguistic Style Control for Expressive Text-to-Speech Generation (Haowei Lou, Hye-young Paik, Wen Hu and Lina Yao)
Hyperspherical Dynamic Multi-Prototype with Arguments Dependencies and Role Consistency for Event Argument Extraction (Xiaojia Huang, Ruifang He, Fei Huang, Bo Wang, Sen Yao and Xiaohong Li)
Do Recommender Systems Really Leverage Multimodal Content? A Comprehensive Analysis on Multimodal Representations for Recommendation (Claudio Pomo, Matteo Attimonelli, Danilo Danese, Fedelucio Narducci and Tommaso Di Noia)
FP15: Fairness 2
FairRegBoost: An End-to-End Data Processing Framework for Fair and Scalable Regression (Nico Lässig and Melanie Herschel)
Enabling Group Fairness in Machine Unlearning via Distribution Correction (Yezi Liu and Yanning Shen)
MMFair: Fair Learning via Min-Min Optimization (Fang Kejie, Zhai Kun and Ma Xingjun)
FairAD: Computationally Efficient Fair Graph Clustering via Algebraic Distance (Minh Phu Vuong, Young-Ju Lee, Ivan Ojeda-Ruiz and Chul-Ho Lee)
FROG: Fair Removal on Graph (Ziheng Chen, Jiali Cheng, Hadi Amiri, Kaushiki Nag, Lu Lin, Sijia Liu, Gabriele Tolomei and Xiangguo Sun)
FedFMD: Fairness-Driven Adaptive Aggregation in Federated Learning via Mahalanobis Distance (Xiuting Weng, Lixing Yu, Shaojie Zhan, Ruizhi Pu and Xiaofei Liu)
FP16: Recommender Systems 3
Compensating Information and Capturing Modal Preferences in Multimodal Recommendation: A Dual-Path Representation Learning Framework (Cairong Yan, Xubin Mao, Zijian Wang, Xicheng Zhao and Linlin Meng)
EEG-FSL: An EEG-Based Few-Shot Learning Framework for Music Recommendation (Ming He, Wenbo Luo, Yongjie Zheng, Junkai Zhang and Xiaolei Gao)
Generative Data Augmentation in Graph Contrastive Learning for Recommendation (Yansong Wang, Qihui Lin, Junjie Huang and Tao Jia)
ExplorAct: Context-Aware Next Action Recommendations for Interactive Data Exploration (Baranadura Dinuka Manohara de Zoysa, James Bailey and Renata Borovica-Gajic)
Enhancing Recommendation with Reliable Multi-profile Alignment and Collaborative-aware Contrastive Learning (Yibin Liu, Jianyu Zhang and Shijian Li)
SarRec: Statistically-guaranteed Augmented Retrieval for Recommendation (Tong Zhang, Nitin Bisht, Zihao Li, Guandong Xu and Xianzhi Wang)
Maximum In-Support Return Modeling for Dynamic Recommendation with Language Model Prior (Xiaocong Chen, Siyu Wang and Lina Yao)
FP17: Graph Learning 3
Dynamic Triangulation-Based Graph Rewiring for Graph Neural Networks (Hugo Attali, Thomas Papastergiou, Nathalie Pernelle and Fragkiskos D. Malliaros)
GegenNet: Spectral Convolutional Neural Networks for Link Sign Prediction in Signed Bipartite Graphs (Hewen Wang, Yang Renchi and Xiaokui Xiao)
Reconsidering the Performance of GAE in Link Prediction (Weishuo Ma, Yanbo Wang, Xiyuan Wang and Muhan Zhang)
Modeling Edge-Specific Node Features through Co-Representation Neural Hypergraph Diffusion (Yijia Zheng and Marcel Worring)
D-HAT: Dynamic Hypergraph Representation Learning with Attention-Based Multi-Level Hypergraph Sampling (Ah-Hyun Lee and Gordon Euhyun Moon)
FinD3: A Dual 3D State Space Model with Dynamic Hypergraph for Financial Stock Prediction (Jieyuan Mei, Jindong Tian, Ronghui Xu, Hanyue Wei, Chenjuan Guo and Bin Yang)
FP18: Machine Learning & AI 3
Flexiffusion: Training-Free Segment-Wise Neural Architecture Search for Efficient Diffusion Models (Hongtao Huang, Xiaojun Chang and Lina Yao)
Invariant Treatment Effect Estimation via Consistent Constraints and Information Bottleneck (Siwei Qiang)
Efficient Mask Learning for Language Model Fine-Tuning (Minping Chen, Ruijia Yang and Zeyi Wen)
MARM: Unlocking the Recommendation Cache Scaling-Law through Memory Augmentation and Scalable Complexity (Xiao Lv, Jiangxia Cao, Shijie Guan, Xiaoyou Zhou, Zhiguang Qi, Yaqiang Zang, Ben Wang and Guorui Zhou)
Streamlining Feature Interactions via Selectively Crossing Vectors for Click-Through Rate prediction (Byungwoo Jang, Jinhee Park and Eunil Park)
Target Item-oriented Conditional Diffusion Differential Transformer for Next-Item Prediction (Xiaoqing Chen, Zitao Xu, Weike Pan and Zhong Ming)
FP19: LLMs 3
Out-of-Source Logs Prevail! A Prior-Free LLM Parser for Unknown System Logs (Chengyu Song, Lin Yang, Jianming Zheng, Jinzhi Liao, Feng Yang, Linru Ma and Fei Cai)
A Cost-Effective Framework to Evaluate LLM-Generated Relevance Judgements (Simone Merlo, Stefano Marchesin, Guglielmo Faggioli and Nicola Ferro)
Trustworthy AI Psychotherapy: Multi-Agent LLM Workflow for Counseling and Explainable Mental Disorder Diagnosis (Mithat Can Ozgun, Jiahuan Pei, Koen Hindriks, Lucia Donatelli, Qingzhi Liu and Junxiao Wang)
Exploring Causal Effect of Social Bias on Faithfulness Hallucinations in Large Language Models (Zhenliang Zhang, Junzhe Zhang, Xinyu Hu, Huixuan Zhang and Xiaojun Wan)
FAIR-SE: Framework for Analyzing Information Disparities in Search Engines with Diverse LLM-Generated Personas (Jaebeom You, Seung-Kyu Hong, Ling Liu, Kisung Lee and Hyuk-Yoon Kwon)
Harnessing Commonsense: LLM-Driven Knowledge Integration for Fine-Grained Sentiment Analysis (Kai Zhang and Yupeng Han)
Unbiased Reasoning for Knowledge-Intensive Tasks in Large Language Models via Conditional Front-Door Adjustment (Bo Zhao, Yinghao Zhang, Ziqi Xu, Yongli Ren, Xiuzhen Zhang, Renqiang Luo, Zaiwen Feng and Feng Xia)
FP20: Data Mining 2
Cequel: Cost-Effective Querying of Large Language Models for Text Clustering (Hongtao Wang, Taiyan Zhang, Renchi Yang and Jianliang Xu)
ACMCG: A Cost-effective Active Clustering with Minimal Constraint Graph (Qiu-Yu Wang, Wen-Bo Xie, Tao Deng, Tian Zou, Xuan-Lin Zhu, Xun Fu and Xin Wang)
Multimodal Sentiment Analysis with Multi-Perspective Thinking via Large Multimodal Models (Juhao Ma, Shuai Xu, Yicong Li and Xiaoming Fu)
EmoPerso: Enhancing Personality Detection with Self-Supervised Emotion-Aware Modelling (Lingzhi Shen, Xiaohao Cai, Yunfei Long, Imran Razzak, Guanming Chen and Shoaib Jameel)
TopKNet:Learning to Perceive the Top-K Pivotal Nodes in Spatio-Temporal Data for Traffic Forecasting (Weilai Zhang and Dongbin Hu)
Deep Modality-Disentangled Prompt Tuning for Few-Shot Multimodal Sarcasm Detection (Soumyadeep Jana, Abhrajyoti Kundu and Sanasam Ranbir Singh)
Bridging Thoughts and Words: Graph-Based Intent-Semantic Joint Learning for Fake News Detection (Zhengjia Wang, Qiang Sheng, Danding Wang, Beizhe Hu and Juan Cao)
FP21: Multimodality
SUMMA: A Multimodal Large Language Model for Advertisement Summarization (Weitao Jia, Shuo Yin, Zhoufutu Wen, Han Wang, Zehui Dai, Kun Zhang, Zhenyu Li, Tao Zeng and Xiaohui Lv)
Retrieval-Augmented Image Captioning via Synthesized Entity-Aware Knowledge Representations (Lin Shen, Chenxu Cui, Jinchao Zhang, Haihui Fan, Haotian Jin and Bo Li)
Hearable Image: On-Device Image-Driven Sound Effect Generation for Hearing What You See (Deokjun Eom, Nahyun Kim, Woohyun Nam, Kyungrae Kim, Chaebin Im and Jungwon Park)
Multimodal Sentiment Analysis via Progressive Fusion of Audio-Visual Affective Descriptions (Lisong Ou and Zhixin Li)
DistillCaps: Enhancing Audio-Language Alignment in Captioning via Retrieval-Augmented Knowledge Distillation (Thinh Pham, Nghiem Diep, Lizi Liao and Binh Nguyen)
Modality Alignment with Multi-scale Bilateral Attention for Multimodal Recommendation (Kelin Ren, Chan-Yang Ju and Dong-Ho Lee)
Interactive Text-to-Visualization: Refining Visualization Outputs Through Natural Language User Feedback (Xubang Xiong, Raymond Chi-Wing Wong and Yuanfeng Song)
FP22: Explainability
X-Troll: eXplainable Detection of State-Sponsored Information Operations Agents (Lin Tian, Xiuzhen Zhang, Myung-Hee Kim, Jennifer Biggs and Marian-Andrei Rizoiu)
Amortized Baseline Selection via Rank-Revealing QR for Efficient Model Explanation (Chanwoo Lee, Youngjin Park, Hyeongeun Lee, Yeeun Yoo, Daehee Han, Junho Choi, Geonhyeong Kim, Nari Kim and Jaesik Choi)
Tilia: Enhancing LIME with Decision Tree Surrogates (Jihang Li, Jiacheng Qiu, Yin-Ping Zhao and Zeyi Wen)
ActiViz: Understanding Sample Selection in Active Learning through Boundary Visualization (Jie Chen, Honghui Du, Dairui Liu, Siteng Ma, Brian Mac Namee and Ruihai Dong)
Online activation Value-aware Clustering and Aggregation for faithful argumentative explanations (Ungsik Kim, Jiho Bae, Sang-Min Choi and Suwon Lee)
From Patterns to Predictions: A Shapelet-Based Framework for Directional Forecasting in Noisy Financial Markets (Juwon Kim, Hyunwook Lee, Hyotaek Jeon, Seungmin Jin and Sungahn Ko)
LatentExplainer: Explaining Latent Representations in Deep Generative Models with Multimodal Large Language Models (Mengdan Zhu, Raasikh Kanjiani, Jiahui Lu, Andrew Choi, Qirui Ye and Liang Zhao)
FP23: Recommender Systems 4
STEP: Stepwise Curriculum Learning for Context-Knowledge Fusion in Conversational Recommendation (Zhenye Yang, Jinpeng Chen, Huan Li, Xiongnan Jin, Xuanyang Li, Junwei Zhang, Hongbo Gao, Kaimin Wei and Senzhang Wang)
Content-Agnostic Moderation for Stance-Neutral Recommendations (Nan Li, Bo Kang and Tijl De Bie)
DT-FedSDC: A Dual-Target Federated Framework with Semantic Enhancement and Disentangled Contrastive Learning for Cross-Domain Recommendation (Shanyang Gao, Shanfeng Wang, Lanyu Yao, Jianzhao Li, Zhao Wang, Maoguo Gong and Ke Pan)
An Embarassingly Simple but Effective Knowledge-enhanced Recommender (Haibo Ye, Zhang Lijun, Yuan Yao and Xinjie Li)
SC-DAG: Semantic-Constrained Diffusion Attacks for Stealthy Exposure Manipulation in Visually-Aware Recommender Systems (Ze Lin, Yuqiu Qian, Xiaodong Li, Ziyu Lyu and Hui Li)
Learning Invariant Reliability under Diverse Contexts for Robust Multimedia Recommendation (Yijun Sheng, Pui Ieng Lei, Yanyan Liu, Ximing Chen and Zhiguo Gong)
Budget and Frequency Controlled Cost-Aware Model Extraction Attack on Sequential Recommenders (Lei Zhou, Min Gao, Zongwei Wang and Yibing Bai)
FP24: Knowledge Graphs 1
Understanding the Embedding Models on Hyper-relational Knowledge Graph (Yubo Wang, Shimin Di, Zhili Wang, Haoyang Li, Fei Teng, Hao Xin and Lei Chen)
Relational Multi-Path Enhancement for Extrapolative Relation Reasoning in Temporal Knowledge Graph (Linlin Zong, Chi Ma, Jiahui Zhou, Xinyue Liu, Wenxin Liang, Xianchao Zhang and Bo Xu)
Differentiable Probabilistic Logic Reasoning For Knowledge Graph Completion (Zhongbin Li, Lixing Yu, Kun Yue and Xinquan Wu)
MRCLQR: A Framework for Logical Query Reasoning Based on Multi-information Relation Constraints (Pengwei Pan, Yu Liu, Jun Ma, Jianfeng Qu, Wen Hua and Yanmei Kang)
CoHN: Context-Aware Hawkes Graph Network for Temporal Knowledge Graph Reasoning (Xiaowei Tian, Xiaoyan Zhang, Xiaofeng Du and Tianbo Lu)
TCPN: Temporal Pyramidal Recurrent Network with Contrastive Learning for Temporal Knowledge Graph Reasoning (Liu Yang, Zixuan Luo, Tingxuan Chen, Zidong Wang and Limin Liu)
FP25: Machine Learning & AI 4
Hierarchy-Consistent Learning and Adaptive Loss Balancing for Hierarchical Multi-label Classification (Ruobing Jiang, Mengzhe Liu, Haobing Liu and Yanwei Yu)
EFU: Enforcing Federated Unlearning via Functional Encryption (Samaneh Mohammadi, Vasileios Tsouvalas, Iraklis Symeonidis, Ali Balador, Tanir Ozcelebi, Francesco Flammini and Nirvana Meratnia)
Efficient Knowledge Graph Unlearning with Zeroth-order Information (Yang Xiao, Ruimeng Ye, Bohan Liu, Xiaolong Ma and Hui Bo)
Dual-Space Masked Reconstruction for Robust Self-Supervised Human Activity Recognition (Shuo Xiao, Jiukai Deng, Chaogang Tang and Zhenzhen Huang)
Lead–LagNet: Exploiting Lead–Lag Dependencies for Cross-Series Temporal Prediction (Zhilong Xie, Jiwen Huang, Shaofei Sheng, Rui Cheng and Qing Li)
Robust Multi-Label Learning with Instance-Dependent Label Noise (You Wu, Yabo Shi, Yizhang Zou and Peipei Li)
FP26: Reinforcement Learning
StepTool: Enhancing Multi-Step Tool Usage in LLMs via Step-Grained Reinforcement Learning (Yuanqing Yu, Zhefan Wang, Weizhi Ma, Shuai Wang, Chuhan Wu, Zhiqiang Guo and Min Zhang)
Temporal Distance-aware Subgoal Generation for Offline Hierarchical Reinforcement Learning (Taegeon Park, Seungho Baek, Jongchan Park, Seungjun Oh and Yusung Kim)
Energy-Guided Diffusion Sampling for Long-Term User Behavior Prediction in Reinforcement Learning-based Recommendation (Xiaocong Chen, Siyu Wang and Lina Yao)
Reinforcement Learning-Driven Generative Retrieval with Semantic-aligned Multi-Layer Identifiers (Bo Xu, Yicen Tian, Xiaokun Zhang, Erchen Yu, Dailin Li, Linlin Zong and Hongfei Lin)
RELINK: Edge Activation for Closed Network Influence Maximization via Deep Reinforcement Learning (Shivvrat Arya, Smita Ghosh, Bryan Maruyama and Venkatesh Srinivasan)
STGS: Spatio-temporal Graph Sparsification Using Reinforcement Learning (Nasrin Shabani, Amin Beheshti, Yuankai Qi, Venus Haghighi, Jin Foo and Jia Wu)
FP27: Data Quality
How Fair is FAIR? Understanding LOD Cloud FAIRness Through Correlation Patterns (Maria Angela Pellegrino and Gabriele Tuozzo)
LiveVal: Real-time and Trajectory-based Data Valuation via Adaptive Reference Points (Jie Xu, Zihan Wu, Cong Wang and Xiaohua Jia)
Multi-Resource-Aware Admission Control for Online Data Processing (Ruoyu Wu, Wei Bao and Hequn Wang)
Chunked Data Shapley: A Scalable Dataset Quality Assessment for Machine Learning (Andreas Loizou and Dimitrios Tsoumakos)
PROXYSAMPLER: Proxy Informativeness Estimation for Efficient Data Selection in Active Learning (Miao-Hui Song, Lan Zhang, Mu Yuan and Yijun Liu)
Mixed data k-anonymization by consistent maximal association and microaggregation (Julien Ah-Pine and Nathaniel Gbenro)
FP28: Time Series Data 1
TANDEM: Temporal Attention-guided Neural Differential Equations for Missingness in Time Series Classification (Yongkyung Oh, Dongyoung Lim, Sungil Kim and Alex Bui)
Structural Entropy-based Multivariate Time Series Forecasting (Xinhui Li, Kun Yue, Lixing Yu and Peizhong Yang)
DANet: A RAG-inspired Dual Attention Model for Few-shot Time Series Prediction (Zimo Wen, Hanwen Hu, Nan Fang, Shiyou Qian and Jian Cao)
Frequency-Conditioned Diffusion Models for Time Series Generation (Seungwoo Jeong, Junghyo Sohn, Jaehyun Jeon and Heung-Il Suk)
EAPformer: Entropy-Aware Patch Transformer for Multivariate Long-Term Time Series Forecasting (Jiahao Ling, Xuan Yang, Shimin Gong and Bo Gu)
Multivariate Wind Power Time Series Forecasting with Noise-Filtering Neural ODEs (Chang Tianyu, Dongming Chen and Dongqi Wang)
PromptTSS: A Prompting-Based Approach for Interactive Multi-Granularity Time Series Segmentation (Ching Chang, Ming-Chih Lo, Wen-Chih Peng and Tien-Fu Chen)
FP29: Privacy & Security 1
SEF-UQR: Scalable and Efficient Privacy-Preserving Federated Updating QR Factorization (Haonan Yuan, Wenyuan Wu and Jingwei Chen)
Rethinking Lipschitzness Data-free Backdoor Defense (Xinyi Wang, Zhiyu Zhu, Zhibo Jin, Huaming Chen and Teng Joon Lim)
KV-Auditor: Auditing Local Differential Privacy for Correlated Key–Value Estimation (Jingnan Xu, Leixia Wang and Xiaofeng Meng)
PP-STAT: An Efficient Privacy-Preserving Statistical Analysis Framework using Homomorphic Encryption (Hyunmin Choi)
Dangerous Language Habits! Exploiting Code-Mixing for Backdoor Attacks on NLP Models (Haotian Jin, Haihui Fan, Jinchao Zhang, Yang Li, Bo Li and Junhao Zhou)
FP30: Personalization 1
Entity-Aware Generative Retrieval for Personalized Contexts (Jihyeong Jeon, Jiwon Lee, Cheol Ryu and U Kang)
MUFFIN: Mixture of User-Adaptive Frequency Filtering for Sequential Recommendation (Ilwoong Baek, Mincheol Yoon, Seongmin Park and Jongwuk Lee)
Improved Personalized Headline Generation via Denoising Fake Interests from Implicit Feedback (Kejin Liu, Junhong Lian, Xiang Ao, Ningtao Wang, Xing Fu, Yu Cheng, Weiqiang Wang and Xinyu Liu)
Ordinal Embedding for Collaborative Filtering: A Unified Regularization for Enhanced Generalization and Interpretability (Jie Yang, Ling Luo, Nestor Cabello and Lars Kulik)
Is This News Still Interesting to You?: Lifetime-aware Interest Matching for News Recommendation (Seongeun Ryu, Yunyong Ko and Sang-Wook Kim)
Personalized Federated Recommendation with Multi-Faceted User Representation and Global Consistent Prototype (Jiaming Qian, Xinting Liao, Xiangmou Qu, Zhihui Fu, Xingyu Lou, Changwang Zhang, Pengyang Zhou, Zijun Zhou, Jun Wang and Chaochao Chen)
FP31: Graph Data Mining 1
Enhancing Contrastive Link Prediction With Edge Balancing Augmentation (Chen-Hao Chang, Hui-Ju Hung, Chia-Hsun Lu and Chih-Ya Shen)
Advancing Graph Isomorphism Tests with Metric Space Indicators: A Tool for Improving Graph Learning Tasks (Shenghui Zhang, Pak Lon Ip, Rongqin Chen, Shunran Zhang and Leong Hou U)
Masked Graph Distance Network for Accurate Subgraph Similarity Computation (Xijuan Liu, Yin Chen, Fan Li, Xiaoyang Wang, Haiyang Hu and Ying Zhang)
Tide: A Time-Wise Causal Debiasing Framework for Generative Dynamic Link Prediction (Xin Zhang, Jianming Zheng, Fei Cai, Zhiqiang Pan, Wanyu Chen, Chonghao Chen and Honghui Chen)
ORCAS: Obfuscation-Resilient Binary Code Similarity Analysis using Dominance Enhanced Semantic Graph (Yufeng Wang, Yuhong Feng, Yixuan Cao, Haoran Li, Haiyue Feng and Yifeng Wang)
LLM-Enhanced Generalized Category Discovery via Dynamic Graph Diffusion (Kangjia Fan, Yilong Zhao, Daifeng Li, Changze Lin, Weijun Zhang and Zhiwen Zhong)
Distributed Computation of k-Vertex Connected Components in Large Scale Networks (Xinchao Hu, Yuan Li, Feng Guo, Shan Huang, Guoli Yang and Yuhai Zhao)
FP32: Transfer Learning 1
STA-GANN: A Valid and Generalizable Spatio-Temporal Kriging Approach (Yujie Li, Zezhi Shao, Chengqing Yu, Tangwen Qian, Zhao Zhang, Yifan Du, Shaoming He, Fei Wang and Yongjun Xu)
GSTBench: A Benchmark Study on the Transferability of Graph Self-Supervised Learning (Yu Song, Zhigang Hua, Yan Xie, Jingzhe Liu, Bo Long and Hui Liu)
ITL-LIME: Instance-Based Transfer Learning for Enhancing Local Explanations in Low-Resource Data Settings (Rehan Raza, Guanjin Wang, Kevin Wong, Hamid Laga and Marco Fisichella)
Dynamic Graph Learning via Historical Information Perception and Multi-Granular Temporal Curriculum Learning (Yuehang Cao, Xiang Zhao, Yang Fang, Yan Pan and Jiuyang Tang)
Structure-Attribute Transformations with Markov Chain Boost Graph Domain Adaptation (Zhen Liu, Yongtao Zhang, Shaobo Ren and Yuxin You)
Efficient Knowledge Transfer from Large to Small Language Models via Low-Overhead Query Mechanism (Faizan Ahemad)
Crocodile: Cross Experts Covariance for Disentangled Learning in Multi-Domain Recommendation (Zhutian Lin, Junwei Pan, Haibin Yu, Xi Xiao, Ximei Wang, Zhixiang Feng, Shifeng Wen, Shudong Huang, Dapeng Liu and Lei Xiao)
FP33: LLM & RecSys 1
Exploring the Limits of Text-Based Collaborative Filtering Using LLMs: Discoveries and Insights (Ruyu Li, Wenhao Deng, Yu Cheng, Zheng Yuan, Jiaqi Zhang and Fajie Yuan)
EvalAgent: Towards Evaluating News Recommender Systems with LLM-based Agents (Guangping Zhang, Peng Zhang, Jiahao Liu, Zhuoheng Li, Dongsheng Li, Hansu Gu, Tun Lu and Ning Gu)
STARec: An Efficient Agent Framework for Recommender Systems via Autonomous Deliberate Reasoning (Chenghao Wu, Ruiyang Ren, Junjie Zhang, Ruirui Wang, Zhongrui Ma, Qi Ye and Wayne Xin Zhao)
Local Large Language Models for Recommendation (Yujin Jeon, Jooyoung Kim and Joonseok Lee)
SELF: Surrogate-light Feature Selection with Large Language Models in Deep Recommender Systems (Pengyue Jia, Zhaocheng Du, Yichao Wang, Xiangyu Zhao, Xiaopeng Li, Yuhao Wang, Qidong Liu, Huifeng Guo and Ruiming Tang)
Autonomous Reasoning-Retrieval for Large Language Model Based Recommendation (Bowen Zheng, Xiaolei Wang, Enze Liu, Xi Wang, Lu Hongyu, Yu Chen, Wayne Xin Zhao and Ji-Rong Wen)
Empowering Denoising Sequential Recommendation with Large Language Model Embeddings (Tongzhou Wu, Yuhao Wang, Maolin Wang, Chi Zhang and Xiangyu Zhao)
FP34: Evaluation & Benchmark
Pedagogy-R1: Pedagogical Large Reasoning Model and Well-balanced Educational Benchmark (Unggi Lee, Jaeyong Lee, Jiyeong Bae, Yeil Jeong, Junbo Koh, Gyeonggeon Lee, Gunho Lee, Taekyung Ahn and Hyeoncheol Kim)
Identifying Critical Segments Affecting Piano Performance Evaluation (Hyerim Jeon and Wen-Syan Li)
Adapting LLMs for Personalized Evaluation of Explanations for Recommendations: A Meta-Learning Approach based on MAML (Yurou Zhao, Yingfei Zhang, Quan Zhou, Shuai Zhang, Wei Lin and Jiaxin Mao)
CLUE: Using Large Language Models for Judging Document Usefulness in Web Search Evaluation (Xingzhu Wang, Erhan Zhang, Yiqun Chen, Jinghan Xuan, Yucheng Hou, Yitong Xu, Ying Nie, Shuaiqiang Wang, Dawei Yin and Jiaxin Mao)
Multi-Source Knowledge Pruning for Retrieval-Augmented Generation: A Benchmark and Empirical Study (Shuo Yu, Mingyue Cheng, Qi Liu, Daoyu Wang, Jiqian Yang, Jie Ouyang, Yucong Luo, Chenyi Lei and Enhong Chen)
EventPuzzle: A Benchmark for Multi-Perspective Event Prediction Based on Event Arguments (Guoxuan Ding, Junhao Zhou, Yuqing Li, Xiaobo Guo, Xin Wang and Daren Zha)
Scenario-Wise Rec: A Multi-Scenario Recommendation Benchmark (Xiaopeng Li, Jingtong Gao, Pengyue Jia, Xiangyu Zhao, Yichao Wang, Wanyu Wang, Yejing Wang, Yuhao Wang, Huifeng Guo and Ruiming Tang)
FP35: Time Series Data 2
Bidirectional Temporal-Aware Modeling with Multi-Scale Mixture-of-Experts for Multivariate Time Series Forecasting (Yifan Gao, Boming Zhao, Haocheng Peng, Hujun Bao, Jiashu Zhao and Zhaopeng Cui)
HRCformer: Hierarchical Recursive Convolution-Transformer with Multi-Scale Adaptive Recalibration for Time Series Forecasting (Dejiang Zhang, Lianyong Qi, Yuwen Liu, Xucheng Zhou, Jianye Xie, Haolong Xiang, Xiaolong Xu, Xuyun Zhang, Yang Cao and Yang Zhang)
WDformer: A Wavelet-Based Differential Transformer Model for Time Series Forecasting (Xiaojian Wang, Chaoli Zhang, Zhonglong Zheng and Yunliang Jiang)
AdaPatch: Adaptive Patch-Level Modeling for Non-Stationary Time Series Forecasting (Kun Liu, Zhongjie Duan, Cen Chen, Yanhao Wang, Dawei Cheng and Yuqi Liang)
SST: Multi-Scale Hybrid Mamba-Transformer Experts for Time Series Forecasting (Xiongxiao Xu, Canyu Chen, Yueqing Liang, Baixiang Huang, Guangji Bai, Liang Zhao and Kai Shu)
Mitigating Distribution Shift in Stock Price Data via Return-Volatility Normalization for Accurate Prediction (Hyunwoo Lee, Jihyeong Jeon, Jaemin Hong and U Kang)
MSOFormer: Multi-scale Transformer with Orthogonal Embedding and Frequency Modeling for Multivariate Time Series Forecasting (Qin Shi, Chu Xu, Zongtang Hu, Dong Shen, Dapeng Sun and Lijun Quan)
FP36: Privacy & Security 2
Seeing Through the Blur: Unlocking Defocus Maps for Deepfake Detection (Minsun Jeon and Simon Woo)
Antelope: Potent and Concealed Jailbreak Attack Strategy (Xin Zhao, Xiaojun Chen and Haoyu Gao)
Vulnerability-Aware Hardening for Secure Privacy-Preserving Record Linkage (Sumayya Ziyad, Peter Christen, Anushka Vidanage, Charini Nanayakkara and Rainer Schnell)
PRIMA: Privacy preserving Multi-dimensional Analytic Approach (Yufei Wang, Cheng Xiang, Pengfei Zhang and Anxing Wei)
Backdoor in Seconds: Unlocking Vulnerabilities in Large Pre-trained Models via Model Editing (Dongliang Guo, Mengxuan Hu, Zihan Guan, Junfeng Guo, Thomas Hartvigsen and Sheng Li)
FP37: Personalization 2
Querier-Aware LLM: Generating Personalized Responses to the Same Query from Different Queriers (Hang Zeng, Chaoyue Niu, Fan Wu, Chengfei Lv and Guihai Chen)
Learning Optimal Personalised Reservation Prices in Impression Ad Auctions with Mixture Density Networks (Dmitrii Moor, Emma Zetterdahl, Paul van Vliet, Zhenwen Dai and Mounia Lalmas)
MPFormer: Adaptive Framework for Industrial Multi-Task Personalized Sequential Retriever (Sun Yijia, Huang Shanshan, Che Linxiao, Lu Haitao, Luo Qiang, Gai Kun and Zhou Guorui)
Higher-order Structure and Semantics-enhanced User Profiling for Recommendation (Yanchao Tan, Xinyi Huang, Zhijun Chen, Hang Lv, Hengyu Zhang, Wei Huang and Guofang Ma)
Transformers are Good Clusterers for Lifelong User Behavior Sequence Modeling (Xingmei Wang, Shiyao Wang, Wuchao Li, Jiaxin Deng, Song Lu, Defu Lian and Guorui Zhou)
Distribution-Guided Auto-Encoder for User Multimodal Interest Cross Fusion (Moyu Zhang, Yongxiang Tang, Yujun Jin, Jinxin Hu and Yu Zhang)
Addressing Personalized Bias for Unbiased Learning to Rank (Zechun Niu, Lang Mei, Liu Yang, Ziyuan Zhao, Qiang Yan, Jiaxin Mao and Ji-Rong Wen)
FP38: Graph Data Mining 2
Structure-prior Informed Diffusion Model for Graph Source Localization with Limited Data (Hongyi Chen, Jingtao Ding, Xiaojun Liang, Yong Li and Xiao-Ping Zhang)
Revisiting the Inner Product Method: Optimizing Sparse Matrix Multiplication via Set Intersection (Zheng Hu, Boyu Yang and Weiguo Zheng)
On the Cross-type Homophily of Heterogeneous Graphs: Understanding and Unleashing (Zhen Tao, Ziyue Qiao, Chaoqi Chen, Zhengyi Yang, Lun Du and Qingqiang Sun)
GraphIAM: Two-Stage Algorithm for Improving Class-Imbalanced Node Classification on Attribute-Missing Graphs (Riting Xia, Chunxu Zhang, Xueyan Liu, Anchen Li and Yan Zhang)
CHEM: Causally and Hierarchically Explaining Molecules (Gyeongdong Woo, Soyoung Cho, Donghyeon Kim, Kimoon Na, Changhyun Kim, Jinhee Choi and Jong-June Jeon)
LinkGPT: Leveraging Large Language Models for Enhanced Link Prediction in Text-Attributed Graphs (Zhongmou He, Jing Zhu, Shengyi Qian, Joyce Chai and Danai Koutra)
FP39: Transfer Learning 2
Contextual Attention Modulation: Towards Efficient Multi-Task Adaptation in Large Language Models (Dayan Pan, Zhaoyang Fu, Jingyuan Wang, Xiao Han, Yue Zhu and Xiangyu Zhao)
TFMAdapter: Lightweight Instance-Level Adaptation of Foundation Models for Forecasting with Covariates (Afrin Dange and Sunita Sarawagi)
High-Order Moments Conditional Domain Adaptation Networks for Wearable Human Activity Recognition (Indrajeet Ghosh, Garvit Chugh, Abu Zaher Md Faridee and Nirmalya Roy)
OASIS: Open-world Adaptive Self-supervised and Imbalanced-aware System (Miru Kim, Mugon Joe and Minhae Kwon)
Parameter-Efficient Transfer Learning for EEG Foundation Models via Task-Relevant Feature Focusing (Jaehyun Jeon, Seungwoo Jeong, Yeajin Shon and Heung-Il Suk)
BrainX: A Universal Brain Decoding Framework with Feature Disentanglement and Neuro-Geometric Representation Learning (Zheng Cui, Dong Nie, Pengcheng Xue, Xia Wu, Daoqiang Zhang and Xuyun Wen)
Transferable Deep Clustering Model (Zheng Zhang and Liang Zhao)
FP40: LLM & RecSys 2
LangPTune: Optimizing Language-based User Profiles for Recommendation (Zhaolin Gao, Joyce Zhou, Yijia Dai and Thorsten Joachims)
PAnDA: Combating Negative Augmentation via Large Language Models for User Cold-Start Recommendations (Yantong Du, Rui Chen, Xiangyu Zhao, Qilong Han and Kai Qin)
Incremental Learning for LLM-based Tokenization and Recommendation (Haihan Shi, Xinyu Lin, Wenjie Wang, Wentao Shi, Junwei Pan, Jie Jiang and Fuli Feng)
Harnessing Large Language Models for Group POI Recommendations (Jing Long, Liang Qu, Junliang Yu, Tong Chen, Hung Nguyen and Hongzhi Yin)
M-LLM^3REC: A Motivation-Aware User-Item Interaction Framework for Enhancing Recommendation Accuracy with LLMs (Lining Chen, Qingwen Zeng and Huaming Chen)
Empowering Large Language Model for Sequential Recommendation via Multimodal Embeddings and Semantic IDs (Yuhao Wang, Junwei Pan, Xinhang Li, Maolin Wang, Yuan Wang, Yue Liu, Dapeng Liu, Jie Jiang and Xiangyu Zhao)
FP41: Performance
Hybrid$^2$: Distributed GNN Training System Enhanced by Dual-Hybrid for Sampling and Loading (Chu Zhao, Shengjie Dong, Yuhai Zhao, Yuan Li, Zhengkui Wang and Xingwei Wang)
ECLIPSE: Efficient Cross-Lingual Log Intelligence Parser with Semantic Entropy-Enhanced LCS Algorithm (Wei Zhang, Xianfu Cheng, Xiang Li, Jian Yang, Liying Zhang, Xiangyuan Guan and Zhoujun Li)
Calibrating on Kolmogorov–Arnold Network (Wenhao Liang, Wei Emma Zhang, Lin Yue, Miao Xu, Olaf Maennel and Weitong Chen)
Exploring Diverse Sparse Network Structures via Dynamic pruning with Weight Alignment (Jinwoo Kim, Jongyun Shin, Sangho An and Jangho Kim)
Adaptive Context-Infused Performance Evaluator for Iterative Feature Space Optimization (Yanping Wu, Yanyong Huang, Zijun Yao, Yanjie Fu, Kunpeng Liu, Xiao Luo and Dongjie Wang)
Efficiency Boost in Decentralized Optimization: Reimagining Neighborhood Aggregation with Minimal Overhead (Durgesh Kalwar, Mayank Baranwal and Harshad Khadilkar)
LEI: Reinforced Multi-Object Cache Admission (Hexuan Lv, Yuhai Zhao and Sice Wang)
FP42: Time Series Data 3
Adaptive Bidirectional State Space Model for High-frequency Portfolio Management (Wei Ding, Hanpeng Jiang, Ruibo Xiong, Yongrong Wu, Jingan Chen, Lifan Chen, Pengfei Ding and Fan Lin)
FinCast: A Foundation Model for Financial Time-Series Forecasting (Zhuohang Zhu, Haodong Chen, Qiang Qu and Vera Chung)
TLCCSP: A Scalable Framework for Enhancing Time Series Forecasting with Time-Lagged Cross-Correlations (Jianfei Wu, Wenmian Yang, Bingning Liu and Weijia Jia)
MillGNN: Learning Multi-Scale Lead-Lag Dependencies for Multi-Variate Time Series Forecasting (Binqing Wu, Zongjiang Shang, Jianlong Huang and Ling Chen)
Give Me Some SALT: Structure-Aware Link Modeling for Temporal Weighted Link Prediction (Ting Li, Hanchen Wang, Yiran Li and Xiaolei Liu)
Neural Instrumented Factorization: Learning Dynamic Asset Pricing Factors and Loadings through Characteristics Control (Ajim Uddin)
DYCOR: Capturing Hidden Stock Relationships for Stock Trend Prediction (Kangmin Choi, Geon Shin, Jungwoo Yang and Hyunjoon Kim)
FP43: Robust & Resilient AI
ROKAN: Toward Interpretable and Domain-Robust Memory Behavior Modeling (Shen Xiaoxuan, Hu Zhihai, Chen Di, Sun Jianwen and Liu Shengyingjie)
Where Do LLMs Go Wrong? Diagnosing Automated Peer Review via Aspect-Guided Multi-Level Perturbation (Jiatao Li, Yanheng Li, Xinyu Hu, Mingqi Gao and Xiaojun Wan)
Towards Reliable GNNs: Adversarial Calibration Learning for Confidence Estimation (Yilong Wang, Jiahao Zhang, Tianxiang Zhao and Suhang Wang)
Robust Heterogeneous GNNs via Semantic Attention and Contrastive Learning (Chongjie Zhao, Jinyan Wang, Linlin Su, Zeming Gan and Ziyang Zhou)
Get Global Guarantees: On the Probabilistic Nature of Perturbation Robustness (Wenchuan Mu and Kwan Hui Lim)
Discovering Group Collapser for Network Resilience (Guozhang Sun, Haoyuan Wang, Yuhai Zhao, Zhengkui Wang, Yuan Li and Xingwei Wang)
FakeChain: Exposing Shallow Cues in Multi-Step Deepfake Detection (Minji Heo and Simon Woo)
FP44: Graph-based Recommendation
SPARK: Adaptive Low-Rank Knowledge Graph Modeling in Hybrid Geometric Spaces for Recommendation (Binhao Wang, Yutian Xiao, Maolin Wang, Zhiqi Li, Tianshuo Wei, Ruocheng Guo and Xiangyu Zhao)
Collaborative Interest Mining Network for Knowledge Graph-based Recommendation (Jie Luo, Ying Pan and Guoliang Huang)
PKGRec: Personal Knowledge Graph Construction and Mining for Federated Recommendation Enhancement (Haochen Yuan, Yang Zhang, Quan Z. Sheng, Lina Yao, Yipeng Zhou, Xiang He and Zhongjie Wang)
Improving the Safety of Medication Recommendation via Graph Augmented Patient Similarity Network (Ming He, Yongjie Zheng, Changle Li and Man Zhou)
Causality-aware Graph Aggregation Weight Estimator for Popularity Debiasing in Top-K Recommendation (Yue Que, Yingyi Zhang, Xiangyu Zhao and Chen Ma)
PriviRec: Confidential and Decentralized Graph Filtering for Recommender Systems (Julien Nicolas, César Sabater, Mohamed Maouche, Mark Coates and Sonia Ben Mokhtar)
FP45: Knowledge Graphs 2
Exploration and Visualization of a Legal Knowledge Graph: A Human-Centered Approach (Sabine Wehnert, Pramod Kumar Bontha, Kilian Lüders, Huu Huong Giang Nguyen and Ernesto William De Luca)
STKGNN: Scalable Spatio-Temporal Knowledge Graph Reasoning for Activity Recognition (Gözde Ayşe Tataroğlu Özbulak, Yash Raj Shrestha and Jean-Paul Calbimonte)
DebiasedKGE: Towards Mitigating Spurious Forgetting in Continual Knowledge Graph Embedding (Junlin Zhu, Bo Fu and Guiduo Duan)
KALE: Knowledge Aggregation for Label-free Model Enhancement (Yuebin Xu, Xuemei Peng, Zhiyi Chen and Zeyi Wen)
Strong Forgetting for ALCQ-Ontologies (Sen Wang and Yizheng Zhao)
A Hierarchical Structure-Enhanced Personalized Recommendation Model for Traditional Chinese Medicine Formulas Based on KG Diffusion Guidance (Chaobo Zhang and Long Tan)
FP46: Natural Language Processing
Extreme Multi-Label Completion for Semantic Document Tagging with Taxonomy-Aware Parallel Learning (Julien Audiffren, Christophe Broillet, Ljiljana Dolamic and Philippe Cudre-Mauroux)
From Menus to the Interactive Food-Ordering Systems (Min-Ji Kim, Seong-Jin Park, Jaehwan Ha, Ju-Won Seo, Dinara Aliyeva and Kang-Min Kim)
Relation-Faceted Graph Pooling with LLM Guidance for Dynamic Span-Aware Information Extraction (Hye-Yoon Baek, Jinho Choi, Jimyeung Seo, Xiongnan Jin, Dongcheon Lee and Byungkook Oh)
Exploring Iterative Refinement for Nested Named Entity Recognition with IoU-aware Denoising Diffusion (Qiaoxuan Yin, Jianquan Ouyang and Huanrong Tang)
Hearing the Meaning, Not the Mess: Beyond Literal Transcription for Spoken Language (Min Sun, Ke Xu, Jiarong Liu, Jifan Yang, Yan Fang, Weizheng Wang, Qipeng Xie, Shuxin Zhong and Kaishun Wu)
Fine-Grained Emotion Recognition via In-Context Learning (Zhaochun Ren, Zhou Yang, Chenglong Ye, Haizhou Sun, Chao Chen, Xiaofei Zhu and Xiangwen Liao)
SwaGNER: Leveraging Span-aware Grid Transformers for Accurate Nested Named Entity Recognition (Seungjoo Lee, Yong-chan Park and U Kang)
FP47: LLM & IR
LLM-Powered Information Extraction for the Dairy Financial Domain: Tackling Data Scarcity and Ambiguity (Chunyan An, Yuying Huang, Qiang Yang, Siyu Yuan and Zhixu Li)
ReCode: Improving LLM-based Code Repair with Fine-Grained Retrieval-Augmented Generation (Yicong Zhao, Shisong Chen, Jiacheng Zhang and Zhixu Li)
BordaRAG: Resolving Knowledge Conflict in Retrieval-Augmented Generation via Borda Voting Process (Yuxin Li, Chen Xu, Jun Xu and Ji-Rong Wen)
Where Does Legal AI Fail? Evaluating RAG Pipelines (Yongjae Kim and Wonjae Lee)
A Comparative Analysis of Linguistic and Retrieval Diversity in LLM-Generated Search Queries (Oleg Zendel, Sara Fahad Dawood Al Lawati, Lida Rashidi, Falk Scholer and Mark Sanderson)
KUG: Joint Enhancement of Internal and External Knowledge for Retrieval-Augmented Generation (Mingyang Li, Shisong Chen, Shengkun Tu, Ziyi Du, Jinghao Zhang, Zhixu Li and Yanghua Xiao)
CLAP: Coreference-Linked Augmentation for Passage Retrieval (Huanwei Xu, Lin Xu and Liang Yuan)
FP48: AI for Science
Docking-Aware Attention: Dynamic Protein Representations through Molecular Context Integration (Amitay Sicherman and Kira Radinsky)
MUSE: A Multi-slice Joint Analysis Method for Spatial Transcriptomics Experiments (Ziheng Duan, Xi Li, Zhiqing Xiao, Rex Ying and Jing Zhang)
Full-Atom Protein-Protein Interaction Prediction via Atomic Equivariant Attention Network (Chunchen Wang, Cheng Yang, Wenchuan Yang, Le Song and Chuan Shi)
Geometric Heterogeneous Graph Neural Network for Protein-Ligand Binding Affinity Prediction (Feng Huang, Yuhang Xia, Ziyan Wang, Liuqing Yang and Wen Zhang)
Towards Fully-Automated Materials Discovery via Large-Scale Synthesis Dataset and Expert-Level LLM-as-a-Judge (Heegyu Kim, Taeyang Jeon, Seungtaek Choi, Ji Hoon Hong, Dong Won Jeon, Ga-Yeon Baek, Gyeong-Won Kwak, Dong-Hee Lee, Jisu Bae, Chihoon Lee, Yunseo Kim, Seon-Jin Choi, Jin-Seong Park, Sung Beom Cho and Hyunsouk Cho)
Unified Molecule Pre-training with Flexible 2D and 3D Modalities: Single and Paired Modality Integration (Tengwei Song, Min Wu and Yuan Fang)
Towards Few-shot Chemical Reaction Outcome Prediction (Yili Shen, Yijun Tian, Cheng-Wei Ju, Olaf Wiest and Xiangliang Zhang)
FP49: Spatio-Temporal Data 1
Stamp: Semantic-Aware Sub-trajectory Anomaly Detection with Diffusion Multi-model Pool for Evolving Data Streams (Biao Chen, Junhua Fang, Pingfu Chao, An Liu, Pengpeng Zhao and Lei Zhao)
GRIT: An Accurate and Efficient Graph Stream Summarization for Temporal Query (Jingxian Hu, Guozhang Sun, Xin Wang, Yuhai Zhao, Yuan Li and Xingwei Wang)
TCFMamba: Trajectory Collaborative Filtering Mamba for Debiased Point-of-Interest Recommendation (Jin Qian, Shiyu Song, Xin Zhang, Dongjing Wang, He Weng, Haiping Zhang and Dongjin Yu)
MGSTDN: Multi-Granularity Spatial-Temporal Diffusion Network for Next POI Recommendation (Zhuang Zhuang, Haitao Yuan, Shanshan Feng, Heng Qi, Yanming Shen and Baocai Yin)
FEDDGCN: A Frequency-Enhanced Decoupling Dynamic Graph Convolutional Network for Traffic Flow Prediction (Wendong Zhang, Ruobai Xiang, Zhifang Liao, Peng Lan and Qihao Liang)
KRAFT: A Knowledge Graph-Based Framework for Automated Map Conflation (Farnoosh Hashemi and Laks Lakshmanan)
Balance and Brighten: A Twin-Propeller Network to Release Potential of Physics Laws for Traffic State Estimation (Weihao Jiang, Yao Fu, Hong Zhao, Xiaoyu Cai, Ruiheng Yang, Linsen Li and Jiang Zhu)
FP50: Social Networks 1
Dual Denoising Diffusion Model for Session-based Social Recommendation (Mengying Lu, Hai-Tao Zheng, Lan Zhou, Qi Li, Jinxiao Shan, Zhixing Li and Hong-Gee Kim)
Usefulness and Diminishing Returns: Evaluating Social Information in Recommender Systems (Qing Meng, Huiyu Min, Mingshan Hee, Roy Ka-Wei Lee, Bingtian Dai and Shuai Xu)
CS-Agent: LLM-based Community Search via Dual-agent Collaboration (Jiahao Hua, Long Yuan, Qingshuai Feng, Qiang Fang and Shan Huang)
CAGCL: A Community-Aware Graph Contrastive Learning Model for Social Bot Detection (Kaihang Wei, Min Teng, Haotong Du, Songxin Wang, Jinhe Zhao and Chao Gao)
Higher-Order Information Matters: A Representation Learning Approach for Social Bot Detection (Min Gao, Qiang Duan, Boen Liu, Yu Xiao, Xin Wang and Yang Chen)
Dynamic User Credibility Prediction: Leveraging State-Aware Neural Processes for Proactive Misinformation Mitigation (Haoran Chen and Dongmei Han)
Variety Is the Spice of Life: Detecting Misinformation with Dynamic Environmental Representations (Bing Wang, Ximing Li, Yiming Wang, Changchun Li, Jiaxu Cui, Renchu Guan and Bo Yang)
FP51: Federated Learning 1
Towards Instance-wise Personalized Federated Learning via Semi-Implicit Bayesian Prompt Tuning (Tiandi Ye, Wenyan Liu, Kai Yao, Lichun Li, Shangchao Su, Cen Chen, Xiang Li, Shan Yin and Ming Gao)
Publicly Verifiable and Fault-Tolerant Privacy-Preserving Aggregation for Federated Learning (Guohao Li, Qi Jiang, Lu Zhou and Li Yang)
Curriculum Guided Personalized Subgraph Federated Learning (Minku Kang and Hogun Park)
MMiC: Mitigating Modality Incompleteness in Clustered Federated Learning (Lishan Yang, Wei Emma Zhang, Michael Sheng, Lina Yao, Weitong Chen and Ali Shakeri)
Advanced Privacy Protection in Federated Learning using Server-initiated Homomorphic Encryption (Cameron Lee, Matthew L. Daggitt, Yansong Gao and Jin B. Hong)
FedSTEP: Asynchronous and Staleness-Aware Personalization for Efficient Federated Learning (Gang Yan, Jian Li and Wan Du)
A Robust Clustered Federated Learning Approach for Non-IID Data with Quantity Skew (Michael Ben Ali, Imen Megdiche, André Péninou and Olivier Teste)
FP52: Sequential Recommendation
TriSeRec: A Tri-view Representation Learning Framework for Sequential/Session-based Recommendation (Xinchen Yuan and Yichao Lu)
Frequency-Domain Disentanglement-Fusion and Dual Contrastive Learning for Sequential Recommendation (Shuo Xiao, Jingtao Zhang, Chaogang Tang and Zhenzhen Huang)
Linking Ordered and Orderless Modeling for Sequential Recommendation (Sijia Li, Min Gao, Zongwei Wang, Yibing Bai and Wuhan Chen)
Continuous Data Augmentation via Condition-Tokenized Diffusion Transformer for Sequential Recommendation (Chenglong Shi, Haosen Wang and Pan Tang)
Enhancing Multi-Behavior Sequential Recommenders with Behavior-Aware Regularization (Yongfu Fan, Jin Chen, Yangzixuan Jiao, Ximu Zeng, Liwei Deng and Kai Zheng)
DPT: Dynamic Preference Transfer for Cross-Domain Sequential Recommendation (Xiang Ying, Rui Ding, Yue Zhao, Mei Yu and Mankun Zhao)
Context-aware Sequential Bundle Recommendation via User-specific Representations (Jaeri Lee and U Kang)
FP53: Graph Neural Networks 1
ADMP-GNN: Adaptive Depth Message Passing GNN (Yassine Abbahaddou, Fragkiskos D. Malliaros, Johannes F. Lutzeyer and Michalis Vazirgiannis)
Empirical Study of Over-Squashing in GNNs and Causal Estimation of Rewiring Strategies (Danial Saber and Amirali Salehi-Abari)
EvoFormer: Learning Dynamic Graph-Level Representations with Structural and Temporal Bias Correction (Haodi Zhong, Liuxin Zou, Di Wang, Bo Wan, Zhenxing Niu and Quan Wang)
SimFormer: Multilevel Transformer on Learnable Mesh Graphs for Engineering Simulation (Jiasheng Shi, Fu Lin, Weixiong Rao and Ze Gao)
Temporal Blocks with Memory Replay for Dynamic Graph Representation Learning (Zhigang Yu, Hao Yan, Ruochen Liu, Xianghan Wang, Haijun Zhang and Senzhang Wang)
LCHGNN: Towards Distributed Hypergraph Neural Network Training Based on Communication Graphs with Lightweight Communication Optimization (Taibo Wang, Yu Gu, Xinning Cui, Zhen Song, Xiaohua Li and Fangfang Li)
PathLens: Structurally Enhancing Heterophilic Graphs for GNNs (Karan Goyal, Saankhya Samanta, Vikram Goyal and Mukesh Mohania)
FP54: Question Answering
Chart-CoCa: Self-Improving Chart Understanding of Vision LMs via Code-Driven Synthesis and Candidate-Conditioned Answering (Gongyao Jiang and Qiong Luo)
Asking Questions with Thoughts: An Efficient Difficulty-Controllable Question Generation Method with Posterior Knowledge Distillation (Sixing Wu, Jiahao Chen, Yujue Zhou, Zhijun Yang and Wei Zhou)
ClariLM: Enhancing Open-domain Clarification Ability for Large Language Models (Ziliang Zhao, Haonan Chen, Shiren Song, Jian Xie and Zhicheng Dou)
Advancing Temporal Sensitive Question Answering through Progressive Multi-Step Reflection (Ziyang Chen, Erxue Min, Xiang Zhao, Yunxin Li, Xin Jia, Jinzhi Liao, Shuaiqiang Wang, Baotian Hu and Dawei Yin)
QGCMA: A Framework for Knowledge-Based Visual Question Answering (Wei Li and Zhixin Li)
Dialogues Aspect-based Sentiment Quadruple Extraction via Structural Entropy Minimization Partitioning (Kun Peng, Cong Cao, Hao Peng, Zhifeng Hao, Lei Jiang, Kongjing Gu, Yanbing Liu and Philip S. Yu)
FP55: LLM & KG
From Anchors to Answers: A Novel Node Tokenizer for Integrating Graph Structure into Large Language Models (Yanbiao Ji, Chang Liu, Xin Chen, Dan Luo, Yue Ding, Mei Li, Wenqing Lin and Hongtao Lu)
LGC-CR: Few-shot Knowledge Graph Completion via Local Global Contrastive Learning and LLM-Guided Refinement (Yiming Xu, Qi Song, Yihan Wang, Wangqiu Zhou and Junli Liang)
GCoder: Improving Large Language Model for Generalized Graph Reasoning (Qifan Zhang, Xiaobin Hong, Jianheng Tang, Nuo Chen, Yuhan Li, Wenzhong Li, Jing Tang and Jia Li)
LLMAEL: Large Language Models are Good Context Augmenters for Entity Linking (Amy Xin, Yunjia Qi, Zijun Yao, Fangwei Zhu, Kaisheng Zeng, Bin Xu, Lei Hou and Juanzi Li)
Reverse Chain-of-Thought and Causal Path Verification: A Modular Plugin for Aligning LLMs with Knowledge Graphs (Dezhuang Miao, Yibin Du, Xiang Li, Xiaoming Zhang, Jiahe Li, Bo Zhang, Bingyu Yan, Lian Zhang and Litian Zhang)
On Verifiable Legal Reasoning: A Multi-Agent Framework with Formalized Knowledge Representations (Albert Sadowski and Jaroslaw A. Chudziak)
Enhancing Multimodal Entity Linking via Distillation and Multimodal Large Language Models (Jintao Huang, Dong Wang, Shasha Li, Yuanxi Peng and Ruochun Jin)
FP56: Search & Retrieval 1
UniECS: Unified Multimodal E-Commerce Search Framework with Gated Cross-modal Fusion (Zihan Liang, Yufei Ma, Zhipeng Qian, Huangyu Dai, Zihan Wang, Ben Chen, Chenyi Lei, Yuqing Ding and Han Li)
Bridging Queries and Tables through Entities in Open-Domain Table Retrieval (Da Li, Keping Bi, Jiafeng Guo and Xueqi Cheng)
SG-Filter: Enhancing Similar Text Retrieval via Hierarchical Summarized-Semantic Index and Adaptive Filtering (Jiancai Ye, Jun Liu, Haoyu Zhang, Maojia Sheng, Tao Yang, Jiaming Xu, Jinhao Li, Yu Wang and Guohao Dai)
OFIA: an Object-centric Fine-grained Alignment Enhancement for Video-Text Retrieval (Zhengqi Huang, Wei Li, Chuang Dong and Mingxin Liu)
DIVAgent: A Diversified Search Agent that Mimics the Human Search Process (Zhirui Deng, Jingfen Qiao, Zhicheng Dou, Ji-Rong Wen and Maarten de Rijke)
Quantization Aware Matryoshka Adaptation: Leveraging Matryoshka Learning, Quantization, and Bitwise Operations for Reduced Storage and Improved Retrieval Speed (Faizan Ahemad)
Exploring the Impact of Warnings on User Perception towards AI-Generated Content in Search Results (Pia Donabauer and David Elsweiler)
FP57: Spatio-Temporal Data 2
Extracting Global Temporal Patterns Within Short Look-Back Windows for Traffic Forecasting (Bo Sun, Zhe Wu, Zhiyuan Deng, Li Su and Qingfang Zheng)
Learnable Orthogonal Decomposition for Non-Regressive Prediction for PDE (Yun Young Choi, Kyujin Han, Joohwan Ko, Sangwook Baek and Seunghwan Lee)
Spatio-Temporal Wavelet Enhanced Attention Mamba for Stock Price Forecasting (Shurui Wang, Wenbo Yan and Ying Tan)
Spatio-Temporal Forecasting under Open-World Missingness with Adaptive Mixture-of-Experts (Chenyu Wu, Zhipeng Ma, Junbo Zhang, Songyu Ke and Yu Zheng)
Mixture of Semantic and Spatial Experts for Explainable Traffic Prediction (Yang Hu, Shaobo Li, Dawen Xia, Zhiheng Zhou, Wenyong Zhang, Huaqing Li, Xingxing Zhang and Senzhang Wang)
Decoder-only Pre-training Enhancement for Spatio-temporal Traffic Forecasting (Tao Yu, Junhong Wan, Yao Fu, Weihao Jiang and Jiang Zhu)
ST-Hyper: Learning High-Order Dependencies Across Multiple Spatial-Temporal Scales for Multivariate Time Series Forecasting (Binqing Wu, Jianlong Huang, Zongjiang Shang and Ling Chen)
FP58: Social Networks 2
Beyond Surface Similarity: A Riemannian Hierarchical Ranking Framework for Sociological Concept Equivalence (Zeqiang Wang, Wing Yan Li, Jon Johnson, Nishanth Sastry and Suparna De)
IPNet: An Interaction Pattern-aware Neural Network for Temporal Link Prediction (Qingyang Zhang, Yitong Wang and Xinjie Lin)
Community Partition-based Source Localization with Adaptive Observers Deployment (Jinchen Shi, Yang Fang, Zhen Tan, Xin Zhang and Xiang Zhao)
Cross-National Collaboration in Open-Source Software Development (Henry Xu, Katy Yu, Hao He, Hongbo Fang, Bogdan Vasilescu and Patrick Park)
Enhancing information diffusion prediction via multiple granularity hypergraphs and position-aware sequence model (Weikai Jing, Yuchen Wang, Haotong Du, Songxin Wang, Xiaoyu Li and Chao Gao)
Community-Aware Social Community Recommendation (Runhao Jiang, Renchi Yang and Wenqing Lin)
FP59: Federated Learning 2
Rethinking Client-oriented Federated Graph Learning (Zekai Chen, Xunkai Li, Yinlin Zhu, Rong-Hua Li and Guoren Wang)
Aggregated Gradients-based Adaptive Learning Rate Design in Federated Learning (Wenhao Yuan and Xuehe Wang)
OFedED: One-shot Federated Learning with Model Ensemble and Dataset Distillation (Xuhui Li, Zhengquan Luo, Zihui Cui, Xin Cao and Zhiqiang Xu)
FedGC: Contrastive-enhanced Subgraph Federated Learning with Grouping Pseudo-Label (Keao Xi, Nannan Wu, Yiming Zhao and Wenjun Wang)
FedGVD: Efficient Federated Graph Learning via Unidirectional Distillation with Dynamic Virtual Nodes (Zhehao Dai, Guojiang Shen, Yuyue Hu, Jiaxin Du, Xiao Han and Xiangjie Kong)
Decoupling Feature Entanglement for Personalized Federated Learning via Neural Collapse (Haizhou Du and Pengfei Li)
HyperGenFL: Hypernetwork-Generated Model Aggregation in Federated Learning (Jerry Chen, Qikai Lu, Ruiqing Tian, Di Niu and Baochun Li)
FP60: Biomedicine & Health
Weakly Supervised Fine-grained Span-Level Framework for Chinese Radiology Report Quality Assurance (Kaiyu Wang, Lin Mu, Zhiyao Yang, Ximing Li, Xiaotang Zhou, Wanfu Gao and Huimao Zhang)
ECG-Doctor: An Interpretable Multimodal ECG Diagnosis Framework Based on Large Language Models (Dongsheng Tian, Junzhe Jiang, Kai Zhang, Changchun Liu, Yu Yuan, Min Gao and Enhong Chen)
Contextual Representation Anchor Network for Mitigating Selection Bias in Few-Shot Drug Discovery (Ruifeng Li, Wei Liu, Xiangxin Zhou, Mingqian Li, Qiang Zhang, Hongyang Chen and Xuemin Lin)
ProtoEHR: Hierarchical Prototype Learning for EHR-based Healthcare Predictions (Zi Cai, Yu Liu, Zhiyao Luo and Tingting Zhu)
Multi-Ontology Integration with Dual-Axis Propagation for Medical Concept Representation (Mohsen Nayebi Kerdabadi, Arya Hadizadeh Moghaddam, Dongjie Wang and Zijun Yao)
Causal Effect Variational Transformer for Public Health Measures and COVID-19 Infection Cluster Analysis (Jinho Kang, Sungjun Lim, Hojun Park, Jiyoung Jung, Jaehun Jung and Kyungwoo Song)
FP61: Graph Neural Networks 2
EvenOddML: Even and Odd Aggregation with Multi-Level Contrastive Learning for Bipartite Graph (Manasvi Aggarwal, Jahnavi Methukumalli, Deepanshu Bagotia and Suhas Power)
Leveraging Vulnerabilities in Temporal Graph Neural Networks via Strategic High-Impact Assaults (Dong Hyun Jeon, Lijing Zhu, Haifang Li, Pengze Li, Jingna Feng, Tiehang Duan, Houbing Herbert Song, Cui Tao and Shuteng Niu)
Fine-grained Graph Rationalization (Zhe Xu, Menghai Pan, Yuzhong Chen, Huiyuan Chen, Yuchen Yan, Mahashweta Das and Hanghang Tong)
Gravity-GNN: Deep Reinforcement Learning Guided Space Gravity-based Graph Neural Network (Huaming Wu, Lei Tian, Chaogang Tang, Pengfei Jiao, Minxian Xu and Huijun Tang)
Ensemble Pruning via Graph Neural Networks (Yuanke Li, Yiyang Liu, Dongmian Zou and Hongfei Wang)
TAGA: Text-Attributed Graph Self-Supervised Learning by Synergizing Graph and Text Mutual Transformations (Zheng Zhang, Yuntong Hu, Bo Pan, Chen Ling and Liang Zhao)
GRLND: A Graph Reinforcement Learning Framework for Network Dismantling (Hongbo Qu, Xu Wang, Yu-Rong Song, Wei Ni, Guo-Ping Jiang and Quan Z. Sheng)
FP62: Conversational Interactions
To Know What User Concerns: Conceptual Knowledge Reasoning for User Satisfaction Estimation in E-Commerce Dialogue Systems (Li Lin, Yaochang Liu, Kaiwen Xia and Shuai Wang)
From Intents to Conversations: Generating Intent-Driven Dialogues with Contrastive Learning for Multi-Turn Classification (Junhua Liu, Yong Keat Tan, Bin Fu and Kwan Hui Lim)
Towards Adaptive Personalized Conversational Information Retrieval (Fengran Mo, Yuchen Hui, Yuxing Tian, Zhaoxuan Tan, Chuan Meng, Zhan Su, Kaiyu Huang and Jian-Yun Nie)
Evolving Graph-Based Context Modeling for Multi-Turn Conversational Retrieval-Augmented Generation (Yiruo Cheng, Hongjin Qian, Fengran Mo, Yongkang Wu, Zhonghua Li, Qi Ye, Ji-Rong Wen and Zhicheng Dou)
High-Context Empathy in Conversations for Large Language Models (Yuyan Chen, Lei Xia, Jinghan Cao, Zhendong Hou, Weinan Dai and Zhixu Li)
ESED: Emotion-Specific Evidence Decomposition for Uncertainty-Aware Multimodal Emotion Recognition in Conversation (Zechang Xiong, Zhenyan Ji, Wenkang Kong, Jiuqian Dai and Shen Yin)
FollowGPT: A Framework of Follow-up Question Generation for Large Language Models via Conversation Log Mining (Ziliang Zhao, Shiren Song and Zhicheng Dou)
FP63: LLM & Time Series
TimeRAG: Enhancing Complex Temporal Reasoning with Search Engine Augmentation (Zhao Wang, Ziliang Zhao and Zhicheng Dou)
Large Model Annotation-Enhanced Spatio-Temporal Fusion Knowledge Tracing Model (Tianyu Cai, Xiaodi Huang, Tao Zhou, Yanting Li and Shenggen Ju)
ST-LINK: Spatially-Aware Large Language Models for Spatio-Temporal Forecasting (Hyotaek Jeon, Hyunwook Lee, Juwon Kim and Sungahn Ko)
DO: An Efficient Deep Reinforcement Learning Approach for Optimal Route with Collective Spatial Keywords (Jiajia Li, Jiming Dong, Lei Li, Yu Yang, Xin Wang and Mengxuan Zhang)
TableTime: Reformulating Time Series Classification as Training-Free Table Understanding with Large Language Models (Jiahao Wang, Mingyue Cheng, Qingyang Mao, Yitong Zhou, Daoyu Wang, Qi Liu, Feiyang Xu and Xin Li)
BALM-TSF: Balanced Multimodal Alignment for LLM-Based Time Series Forecasting (Shiqiao Zhou, Holger Schöner, Huanbo Lyu, Edouard Fouché and Shuo Wang)
Seeing Sequences like Humans: Pattern Classification Driven Time-Series Forecasting via Vision Language Models (Xingyu Liu, Min Gao, Zongwei Wang and Yinbing Bai)
FP64: Search & Retrieval 2
Dense Retrieval for Aggregated Search (Lang Mei, Sijie Liu, Ziyuan Zhao, Rolan Yan, Jiaxin Mao and Ji-rong Wen)
Scaling Trust: Veracity-Driven Defect Detection in Entity Search (Ornella Irrera, Stefano Marchesin, Gianmaria Silvello and Omar Alonso)
Improving Complex Compositional Query Representations with Learned Sparse Retrievers (Antonios Minas Krasakis, Andrew Yates and Evangelos Kanoulas)
Improving text embedding models with positive-aware hard-negative mining (Gabriel de Souza Pereira Moreira, Radek Osmulski, Mengyao Xu, Ronay Ak, Benedikt Schifferer and Even Oldridge)
Unsupervised Adversarial Contrastive Hashing for Cross-Modal Retrieval (Guohui Ding, Zhonghua Li, Rui Zhou and Qian Gao)
Generalizing Query Performance Prediction under Retriever and Concept Shifts via Data-driven Correction (Jaehwan Jung and Jong-June Jeon)
UniROM: Unifying Online Advertising Ranking as One Model (Junyan Qiu, Ze Wang, Fan Zhang, Zuowu Zheng, Jile Zhu, Jiangke Fan, Teng Zhang, Haitao Wang and Xingxing Wang)
FP65: Urban Systems
Forecasting at Full Spectrum: Holistic Multi-Granular Traffic Modeling under High-Throughput Inference Regimes (Zhaoyan Wang, Xiangchi Song and In-Young Ko)
HGAurban: Heterogeneous Graph Autoencoding for Urban Spatial-Temporal Learning (Qianru Zhang, Xinyi Gao, Haixin Wang, Dong Huang, Siu-Ming Yiu and Hongzhi Yin)
Revisiting Trajectories to Road: A New Diffusion Model and A New Dataset with 1,000,000,000 Points (Yang Wang, Miaomiao Li and Jiazhi Ni)
DSETA: Driving Style-Aware Estimated Time of Arrival (Bolin Zhang and Zhidan Liu)
CityLight: A Neighborhood-inclusive Universal Model for Coordinated City-scale Traffic Signal Control (Jinwei Zeng, Chao Yu, Xinyi Yang, Wenxuan Ao, Qianyue Hao, Jian Yuan, Yong Li, Yu Wang and Huazhong Yang)
Traffic Safety Evaluation Based on Macroscopic Traffic Features in Road Tunnels (Yupu Zhang, Lei Jia, Hao Miao, Weizhu Qian, Yan Zhao and Kai Zheng)
Urban In-context Learning: A New Paradigm for Urban Indicator Prediction (Zerong Deng, Liangze Han, Tongyu Zhu, Ziqi Miao, Yi Xu and Leilei Sun)
ARS Sessions
ARS1: Spatial Learning and Intelligence
Spatial Semantic-based Enhanced Address Parsing via Adaptive Weighted Learning (Huiling Qin, Ming Wang, Yuanxun Li, Junbo Zhang and Yu Zheng)
GeoIndia V2: A Unified Graph and Language Model for Context-Aware Geocoding (Arpit Tiwari, Bhavuk Singhal, Anshu Aditya, Shubham Jain, Debashis Mukherjee and Debdoot Mukherjee)
GCVPN: A Graph Convolutional Visual Prior-Transform Network for Actual Occluded Image Recognition (Lei Wang, Nannan Wu, Huaming Wu, Wei Yu, Fan Zhang and Shuo Chen)
Waypoint POI Recommendation for Vehicle Navigation Services using Hierarchical Graphs and Contrastive Learning (Jongsoo Lee, Heejun Shin, Namhyuk Kim and Dong-Kyu Chae)
Smart ECU: Scalable On-Vehicle Deployment of Drivetrain Fault Classification Systems for Commercial Electric Vehicles (Jaeho Kim, Kwangryeol Park, Kyu Hwan Lee, Jeongmin Oh, Dongjin Park, Hyunseok Oh, Youngrock Chung, Kyung-Woo Lee, Dae-Un Sung and Seulki Lee)
Anomaly Detection for Advanced Driver Assistance System with NCDE-based Normalizing Flow (Kangjun Lee, Minha Kim, Youngho Jun and Simon Woo)
Bridging the Gap Between Sparsity and Redundancy: A Dual-Decoding Framework with Global Context for Map Inference (Yudong Shen, Jiali Mao, Wenyu Wu, Yixiao Tong, Guoping Liu and Chaoya Wang)
ARS2: User Modeling and Engagement Prediction
Pantheon: Personalized Multi-objective Ensemble Sort via Iterative Pareto Policy Optimization (Jiangxia Cao, Pengbo Xu, Yin Cheng, Kaiwei Guo, Jian Tang, Shijun Wang, Dewei Leng, Shuang Yang, Zhaojie Liu, Yanan Niu, Guorui Zhou and Kun Gai)
SMTIR: Scenario-Aware Multi-Trigger Induction Network for CTR Prediction (Xuan Ma, Yu Shi, Hao Peng, Jia Duan, Zhanhao Ye, Kunyao Wang, Kai Yan, Long Chen, Zehua Zhang, Changping Peng, Zhangang Lin and Ching Law)
InterFormer: Effective Heterogeneous Interaction Learning for Click-Through Rate Prediction (Zhichen Zeng, Xiaolong Liu, Mengyue Hang, Xiaoyi Liu, Qinghai Zhou, Chaofei Yang, Yiqun Liu, Yichen Ruan, Laming Chen, Yuxin Chen, Yujia Hao, Jiaqi Xu, Jade Nie, Xi Liu, Buyun Zhang, Wei Wen, Siyang Yuan, Hang Yin, Xin Zhang, Kai Wang, Wen-Yen Chen, Yiping Han, Huayu Li, Chunzhi Yang, Bo Long, Philip S. Yu, Hanghang Tong and Jiyan Yang)
Towards Unbiased and Real-Time Staytime Prediction for Live Streaming Recommendation (Haiyuan Zhao, Changshuo Zhang, Yang Wang, Hao Wang, Bin Yuan, Qinglei Wang and Zuotao Liu)
See Beyond a Single View: Multi-Attribution Learning Leads to Better Conversion Rate Prediction (Sishuo Chen, Zhangming Chan, Xiang-Rong Sheng, Lei Zhang, Sheng Chen, Chenghuan Hou, Han Zhu, Jian Xu and Bo Zheng)
An LLM-based Behavior Modeling Framework for Malicious User Detection (Meng Jiang, Wenjie Wang, Chongming Gao, Shaofeng Hu, Kaishen Ou, Hui Lin and Fuli Feng)
Fraudulent Delivery Detection with Multimodal Courier Behavior Data in Last-Mile Delivery (Shanshan Wang, Sijing Duan, Shuxin Zhong, Zhiqing Hong, Zhiyuan Zhou, Hongyu Lin, Weijian Zuo, Desheng Zhang and Yi Ding)
ARS3: Forecasting and Operational Optimization
AutoDW-TS: Automated Data Wrangling for Time-Series Data (Lei Liu, So Hasegawa, Shailaja Keyur Sampat, Mehdi Bahrami, Wei-Peng Chen, Kodai Toyota, Takashi Kato, Takumi Akazaki, Akira Ura and Tatsuya Asai)
Out of Distribution Detection for Efficient Continual Learning in Quality Prediction for Arc Welding (Yannik Hahn, Jan Voets, Antonin Königsfeld, Hasan Tercan and Tobias Meisen)
OASIS: Harnessing Diffusion Adversarial Network for Ocean Salinity Imputation using Sparse Drifter Trajectories (Bo Li, Yingqi Feng, Ming Jin, Xin Zheng, Yufei Tang, Laurent Cherubin, Can Wang, Alan Wee-Chung Liew, Qinghua Lu, Jingwei Yao, Hong Zhang, Shirui Pan and Xingquan Zhu)
SolarMAE: a unified framework for regional centralized and distributed solar power forecasting with weather pre-training (Jin Wang, Bingqing Peng, Wenwei Wang, Yuanjie Hu, Yuejiang Chen, Peisong Niu and Liang Sun)
D3-TR: Data-driven Daily Delivery Task Rescheduling for Cost-effective Last-mile Delivery (Lidi Zhang, Yinfeng Xiang, Wenjun Lyu, Zhiqing Hong, Haotian Wang, Desheng Zhang, Yunhuai Liu and Tian He)
Development of Autonomous Failure Maintenance System for Semiconductor Manufacturing (Nuri Han, Jiwon Seo, Jonghee Ha, Jihyung Oh, Jinwoo Lee, Boram Jeong, Jongbin Park, Gilhwan Kim and Yohwan Joo)
DeepAries: Adaptive Rebalancing Interval Selection for Enhanced Portfolio Selection (Jinkyu Kim, Hyungjung Yi, Mogan Gim, Donghee Choi and Jaewoo Kang)
ARS4: Research, Retrieval and Ranking in Online Platforms
Beyond Pairwise Learning-To-Rank At Airbnb (Malay Haldar, Daochen Zha, Huiji Gao, Liwei He and Sanjeev Katariya)
Augmenting Guest Search Results with Recommendations at Airbnb (Haowei Zhang, Philbert Lin, Dishant Ailawadi, Soumyadip Banerjee, Shashank Dabriwal, Hao Li, Kedar Bellare, Liwei He and Sanjeev Katariya)
Leveraging Generative Models for Real-Time Query-Driven Text Summarization in Large-Scale Web Search (Zeyu Xiong, Yixuan Nan, Li Gao, Hengzhu Tang, Shuaiqiang Wang, Junfeng Wang and Dawei Yin)
FLAIR: Feedback Learning for Adaptive Information Retrieval (William Zhang, Yiwen Zhu, Yunlei Lu, Mathieu Demarne, Wenjing Wang, Kai Deng, Nutan Sahoo, Katherine Lin, Miso Cilimdzic and Subru Krishnan)
Maps Ranking Optimization in Airbnb (Hongwei Zhang, Malay Haldar, Kedar Bellare, Sherry Chen, Soumyadip Banerjee, Xiaotang Wang, Mustafa Abdool, Huiji Gao, Pavan Tapadia, Liwei He, Sanjeev Katariya and Stephanie Moyerman)
Learning to Comparison-Shop (Jie Tang, Daochen Zha, Xin Liu, Huiji Gao, Liwei He, Stephanie Moyerman and Sanjeev Katariya)
Locale-Aware Product Type Prediction for E-commerce Search Queries (Anna Tigunova, Thomas Ricatte and Ghadir Eraisha)
ARS5: Optimization for Ads and Promotions in E-commerce
MOHPER: Multi-objective Hyperparameter Optimization Framework for E-commerce Retrieval System (Jungbae Park and Heonseok Jang)
Expert-Guided Diffusion Planner for Auto-bidding (Yunshan Peng, Wenzheng Shu, Jiahao Sun, Yanxiang Zeng, Jinan Pang, Wentao Bai, Yunke Bai, Xialong Liu and Peng Jiang)
Dynamic Network-Based Two-Stage Time Series Forecasting for Affiliate Marketing (Zhe Wang, Yaming Yang, Ziyu Guan, Bin Tong, Rui Wang, Wei Zhao and Hongbo Deng)
Augmenting Limited and Biased RCTs through Pseudo-Sample Matching-Based Observational Data Fusion Method (Kairong Han, Weidong Huang, Taiyang Zhou, Peng Zhen and Kun Kuang)
Next-Generation Price Recommendation with LLM-Augmented Graph Transformers (Hadi Mohammadzadeh Abachi, Amin Beheshti, Milad Mosharraf, Pooyan Asgari and Majid Namazi)
Converted Data is All You Need for Causal Optimization of e-Commerce Promotions (Dmitri Goldenberg, Hugo Manuel Proenca, Amit Livne, Felipe Moraes, Javier Albert and Bracha Shapira)
ARS6: Finance, Market and Risk Analytics
SSH-T^3 : A Hierarchical Pre-training Framework for Multi-Scenario Financial Risk Assessment (Zehao Gu, Yateng Tang, Jiarong Xu, Siwei Zhang, Xuehao Zheng, Xi Chen and Yun Xiong)
THEME: Enhancing Thematic Investing with Semantic Stock Representations and Temporal Dynamics (Hoyoung Lee, Wonbin Ahn, Suhwan Park, Jaehoon Lee, Minjae Kim, Sungdong Yoo, Taeyoon Lim, Woohyung Lim and Yongjae Lee)
SCAlign: Transaction Event Prediction via Multi-Scale Market Dynamics Alignment (Boyang Li, Lingzheng Zhang, Fugee Tsung and Xi Zhang)
Zipf-Gramming: Scaling Byte N-Grams Up to Production Sized Malware Corpora (Edward Raff, Ryan Curtin, Derek Everett, Robert Joyce and James Holt)
Towards Explainable Transaction Risk Analysis With Dual Graph Retrieval Augmented Generation (Liang Su, Mingyang Zhang, Kangxiang Jia, Tengfei Liu, Weiqiang Wang, Yun Xiong, Xixi Wu, Xinyu Gao, Yongrui Fu and Jiawei Zhang)
FinSage: A Multi-aspect RAG System for Financial Filings Question Answering (Xinyu Wang, Jijun Chi, Zhenghan Tai, Tung Sum Thomas Kwok, Hailin He, Zhuhong Li, Yuchen Hua, Muzhi Li, Peng Lu, Suyucheng Wang, Wu Yihong, Huang Jerry, Jingrui Tian, Fengran Mo, Yufei Cui and Ling Zhou)
Neighbor-enhanced Graph Pre-training and Prompt Learning Framework for Fraud Detection (Ziyang Cheng, Jie Yang, Yixin Song, Dawei Cheng, Guang Yang and Bo Wang)
ARS7: Graph Learning and Relational Modeling
GOProteinGNN: Leveraging Protein Knowledge Graphs for Protein Representation Learning (Dan Kalifa, Uriel Singer and Kira Radinsky)
Uncovering Corporate Influence: A First Scalable Method for Qualifying Holdings Computation (Livia Blasi, Matteo Brandetti, Costanza Catalano, Andrea Gentili and Davide Magnanimi)
LinkML for Collaborative Petrochemical Knowledge Graph Development (Annie Shoup, Adam Russell and Gavin Nicol)
Let Topology Speak: Graph Neural Network with Topology-Aware Augmentation (Kangzhuo Chen, Xiaoqian Sun, Huawei Shen and Xueqi Cheng)
Cross-Domain Graph Neural Networks for Notification at LinkedIn (Shihai He, Julie Choi, Tianqi Li, Zhiwei Ding, Peng Du, Priya Bannur, Franco Liang, Fedor Borisyuk, Padmini Jaikumar, Xiaobing Xue and Viral Gupta)
Heterogeneous Influence Maximization in User Recommendation (Hongru Hou, Jiachen Sun, Wenqing Lin, Wendong Bi, Xiangrong Wang and Deqing Yang)
Edge-Variational Graph Neural Networks: Harnessing Weak Ties for Enhanced Default Risk Prediction (Feng Zhang, Jianfeng Chi, Rui Ma, Gang Chen and Rongqi Chen)
ARS8: LLMs for Reasoning and Information Retrieval
On the Gap Between Diffusion and Transformer Multi-Tabular Generation (Gijs Paardekooper, Jeroen Galjaard and Lydia Chen)
FR-LoRA: Fisher Regularized LoRA for Multilingual Continual Learning (Sayanta Adhikari, Sanjay Agrawal and Vivek Sembium)
ICLFORGE: Enhancing In-Context Learning with Evolutionary Algorithms under Budgeted Annotation (Vijit Malik, Atul Pande and Anirban Majumder)
AutoCoRe-FL: Automatic Concept-based Rule Reasoning in Federated Learning (Ahmed Soliman and Radwa El Shawi)
Reference-Aligned Retrieval-Augmented Question Answering over Heterogeneous Proprietary Documents (Nayoung Choi, Grace Byun, Andrew Chung, Ellie Paek, Shinsun Lee and Jinho Choi)
Exploring Database Normalization Effects on SQL Generation (Ryosuke Kohita)
ARS9: Representation Learning and Cold-Start Solutions
Stratified Expert Cloning for Retention-Aware Recommendation at Scale (Chengzh Lin, Annan Xie, Shuchang Liu, Wuhong Wang, Chuyuan Wang, Yongq Li and Han Li)
Meta-Adaptive Network for Effective Cold-Start Recommendation via Warm-Aware Representation Learning (Ao Zhang, Boya Du, Yulin Xu, Jialin Zhu and Yuning Jiang)
DAS: Dual-Aligned Semantic IDs Empowered Industrial Recommender System (Wencai Ye, Mingjie Sun, Shaoyun Shi, Peng Wang, Wenjin Wu and Peng Jiang)
CSRM-LLM: Embracing Multilingual LLMs for Cold-Start Relevance Matching in Emerging E-commerce Markets (Yujing Wang, Yiren Chen, Huoran Li, Chunxu Xu, Yuchong Luo, Xianghui Mao, Cong Li, Lun Du, Chunyang Ma, Qiqi Jiang, Yin Wang, Fan Gao, Wenting Mo, Pei Wen, Shantanu Kumar, Taejin Park, Yiwei Song, Vijayendrasastha Rajaram, Tao Cheng, Sonu Durgia and Pranam Kolari)
Prompt Tuning as User Inherent Profile Inference Machine (Yusheng Lu, Zhaocheng Du, Xiangyang Li, Pengyue Jia, Yejing Wang, Weiwen Liu, Yichao Wang, Huifeng Guo, Ruiming Tang, Zhenhua Dong, Yongrui Duan and Xiangyu Zhao)
LinkedIn Post Embeddings: Industrial Scale Embedding Generation and Usage across LinkedIn (Sudarshan Srinivasa Ramanujam, Akanksha Bindal, Tina Jiang, Timothy Hazen, David Golland, Fengyu Zhang, Daqi Sun, Wanning Li, Birjodh Tiwana, Siddharth Dangi and Peng Yan)
ARS10: Generative and Retrieval-Enhanced Recommendation
TRAWL: External Knowledge-Enhanced Recommendation with LLM Assistance (Weiqing Luo, Chonggang Song, Lingling Yi and Gong Cheng)
You Only evaLuate Once: A Tree-based Rerank Method at Meituan (Shuli Wang, Yinqiu Huang, Changhao Li, Yuan Zhou, Yonggang Liu, Yongqiang Zhang, Yinhua Zhu, Haitao Wang and Xingxing Wang)
GReF: A Unified Generative Framework for Efficient Reranking via Ordered Multi-token Prediction (Zhijie Lin, Zhuofeng Li, Chenglei Dai, Wentian Bao, Shuai Lin, Enyun Yu, Haoxiang Zhang and Liang Zhao)
TBGRecall: A Generative Retrieval Model for E-commerce Recommendation Scenarios (Zida Liang, Changfa Wu, Dunxian Huang, Weiqiang Sun, Ziyang Wang, Yuliang Yan, Jian Wu, Yuning Jiang, Bo Zheng, Ke Chen, Silu Zhou and Yu Zhang)
Taming Ultra-Long Behavior Sequence in Session-wise Generative Recommendation (Wuchao Li, Shiyao Wang, Kuo Cai, Jiaxin Deng, Xingmei Wang, Qigen Hu, Defu Lian and Guorui Zhou)
PRECISE: Pre-training and Fine-tuning Sequential Recommenders with Collaborative and Semantic Information (Chonggang Song, Chunxu Shen, Hao Gu, Yaoming Wu, Lingling Yi, Jie Wen and Chuan Chen)
ARS11: Advances in Industrial-Scale Recommendation
HIT Model: A Hierarchical Interaction-Enhanced Two-Tower Model for Pre-Ranking Systems (Haoqiang Yang, Congde Yuan, Kun Bai, Mengzhuo Guo, Wei Yang and Chao Zhou)
RankMixer: Scaling Up Ranking Models in Industrial Recommenders (Jie Zhu, Zhifang Fan, Xiaoxie Zhu, Yuchen Jiang, Hangyu Wang, Xintian Han, Haoran Ding, Xinmin Wang, Wenlin Zhao, Zhen Gong, Huizhi Yang, Zheng Chai, Zhe Chen, Yuchao Zheng, Qiwei Chen, Feng Zhang, Xun Zhou, Peng Xu, Xiao Yang, Di Wu and Zuotao Liu)
Billion-Scale Graph Deep Learning Framework for Ads Recommendation at Meta (Si Zhang, Weilin Cong, Dongqi Fu, Andrey Malevich, Hao Wu, Baichuan Yuan, Xin Zhou, Kaveh Hassani, Zhigang Hua, Austin Derrow-Pinion, Yan Xie, Xuewei Wang, Yinglong Xia, Ning Yao, Vena Li, Sem Park and Bo Long)
Climber: Toward Efficient Scaling Laws for Large Recommendation Models (Songpei Xu, Shijia Wang, Da Guo, Xianwen Guo, Qiang Xiao, Bin Huang, Guanlin Wu and Chuanjiang Luo)
MTGR: Industrial-Scale Generative Recommendation Framework in Meituan (Ruidong Han, Bin Yin, Shangyu Chen, He Jiang, Fei Jiang, Xiang Li, Chi Ma, Mincong Huang, Xiaoguang Li, Chunzhen Jing, Yueming Han, Meilei Zhou, Lei Yu, Chuan Liu and Wei Lin)
NeighSqueeze: Compact Neighborhood Grouping for Efficient Billion-Scale Heterogeneous Graph Learning (Xinyue Feng, Shuxin Zhong, Jinquan Hang, Yuequn Zhang, Guang Yang, Haotian Wang, Desheng Zhang and Guang Wang)
Retrieval-LTV: Fine-Grained Transfer Learning for LTV Estimation in Large-Scale Industrial Ads Retrieval (Shirui Wang, Shengbin Jia, Tianyue Cao, Shuo Yang, Lei Jiang, Qi He, Lingling Yao and Yang Xiang)
ARS12: Multimodal Interaction and Human-Centered AI
DINOCOMPANION: An Attachment-Theory Informed Multimodal Robot for Emotionally Responsive Child-AI Interaction (Boyang Wang, Yuhao Song, Jinyuan Cao, Peng Yu, Hongcheng Guo and Zhoujun Li)
Thematic Bottleneck Models for Multimodal Analysis of School Attendance (Tingrui Qiao, Caroline Walker, Chris Cunningham, Adam Jang-Jones, Susan Morton, Kane Meissel and Yun Sing Koh)
VocQuiz: Vocabulary Question Generation for English Language Education (Yongqi Li, Jiajun Wu, Shangqing Tu, Jifan Yu, Huiqin Liu, Lei Hou and Juanzi Li)
T-Stars-Poster: A Framework for Product-Centric Advertising Image Design (Hongyu Chen, Min Zhou, Jing Jiang, Jiale Chen, Yang Lu, Zihang Lin, Bo Xiao, Tiezheng Ge and Bo Zheng)
When Words Can't Capture It All: Towards Video-Based User Complaint Text Generation with Multimodal Video Complaint Dataset (Sarmistha Das, R E Zera Marveen Lyngkhoi, Kirtan Jain, Vinayak Goyal, Sriparna Saha and Manish Gupta)
EduCraft: A System for Generating Pedagogical Lecture Scripts from Long-Context Multimodal Presentations (Yucheng Wang, Jifan Yu, Daniel Zhang-Li, Joy Jia Yin Lim, Shangqing Tu, Haoxuan Li, Zhiyuan Liu, Huiqin Liu, Lei Hou, Juanzi Li and Bin Xu)
Building A Virtual Member of a Community of Practice (Joshua Eckroth, Dayne Freitag, Jonathan Keefe, Timothy Meyer, Karen Myers, Eric Schoen, Pedro Sequeira and Reid Smith)
ARS13: Multi-Modal and Personalized User Modeling
Personalized Multi Modal Alignment Encoding for CTR-Recommendation in WeChat (Jiawei Zheng, Hao Gu, Lingling Yi, Jie Wen and Chuan Chen)
Audience-Aware and Self-Adaptive Multi-Interest Modeling for Sharing Rate Prediction in Affiliate Marketing (Zhe Wang, Ziyu Guan, Yujian Cao, Yaming Yang, Rui Wang, Bin Tong, Wei Zhao and Hongbo Deng)
MISS: Multi-Modal Tree Indexing and Searching with Lifelong Sequential Behavior for Retrieval Recommendation (Chengcheng Guo, Junda She, Kuo Cai, Shiyao Wang, Qigen Hu, Qiang Luo, Guorui Zhou and Kun Gai)
Progressive Semantic Residual Quantization for Multimodal-Joint Interest Modeling in Music Recommendation (Shijia Wang, Tianpei Ouyang, Qiang Xiao, Dongjing Wang, Yintao Ren, Songpei Xu, Da Guo and Chuanjiang Luo)
QARM: Quantitative Alignment Multi-Modal Recommendation at Kuaishou (Xinchen Luo, Jiangxia Cao, Tianyu Sun, Jinkai Yu, Rui Huang, Wei Yuan, Hezhen Lin, Yichen Zheng, Shiyao Wang, Qigen Hu, Changqing Qiu, Jiaqi Zhang, Xu Zhang, Zhiheng Yan, Jingming Zhang, Simin Zhang, Mingxing Wen, Zhaojie Liu and Guorui Zhou)
BiListing: Modality Alignment for listings (Guillaume Guy, Mihajlo Grbovic, Chun How Tan and Han Zhao)
Personalized Tree based progressive regression model for watch-time prediction in short video recommendation (Xiaokai Chen, Xiao Lin, Changcheng Li and Peng Jiang)
ARS14: LLM/MLLM and Generative AI Applications
RottenReviews: Benchmarking Review Quality with Human and LLM-Based Judgments (Sajad Ebrahimi, Soroush Sadeghian, Ali Ghorbanpour, Negar Arabzadeh, Sara Salamat, Muhan Li, Hai Son Le, Mahdi Bashari and Ebrahim Bagheri)
CheckDAPR: An MLLM-based Sketch Analysis System for Draw-A-Person-in-the-Rain Assessments (Migyeong Yang, Chaehee Park, Taeeun Kim, Hayeon Song and Jinyoung Han)
EnhanceMyPrompt: Rewriting Chat Queries for Effective Response Generation from LLMs (Tushar Abhishek, Manas Jain, Shishir Hardia, Shreevignesh Suriyanarayanan, Sandra Anil, Rushabh Gandhi and Manish Gupta)
End-to-end Information Extraction from Archival Records with Multimodal Large Language Models (Mahsa Vafaie, Sven Hertling, Inger Banse, Kevin Dubout and Harald Sack)
MHSNet:An MoE-based Hierarchical Semantic Representation Network for Accurate Duplicate Resume Detection with Large Language Model (Yu Li, Zulong Chen, Wenjian Xu, Hong Wen, Yipeng Yu, Manlung Yiu and Yuyu Yin)
HuggingGraph: Understanding the Supply Chain of LLM Ecosystem (Mohammad Shahedur Rahman, Peng Gao and Yuede Ji)
Industry Day Sessions
Industry Day 1: Infrastructure and Emerging Applications
AutoRuleSQL: Hybrid Text-to-SQL via Rule-Driven Fast Paths and LLM Bootstrapping (Han Xu, Yang Li, Yanhai Xiong, Robert Mintern, Amir Louka and Haipeng Chen)
Reliable and Efficient Container Orchestration of LLMs via MCP (Han Xu, Yang Li, Yanhai Xiong, Robert Mintern, Amir Louka and Haipeng Chen)
Motion-Based Bird-UAV Classification Using 3D-CNN for Long-Range Anti-UAV Systems (Woo-Choel Jin, Daegun Oh, Sang-Chul Lee and Ji-Woong Choi)
Industry Day 2: Recommendation and Retrieval Systems
TransAct V2: Lifelong User Action Sequence Modeling on Pinterest Recommendation (Xue Xia, Saurabh Joshi, Kousik Rajesh, Kangnan Li, Yangyi Lu, Nikil Pancha, Dhruvil Badani, Jiajing Xu and Pong Eksombatchai)
Autoregressive Generative Retrieval for Industrial-Scale Recommendations at Pinterest (Prabhat Agarwal, Anirudhan Badrinath, Laksh Bhasin, Jaewon Yang, Jiajing Xu and Charles Rosenberg)
Semantic Filter Recommendation for eCommerce Search (Kilian Merkelbach and Antonino Freno)
Industry Day 3: Trust and Safety AI
Building Trustworthy Peer Review Quality Assessment Systems (Negar Arabzadeh, Sajad Ebrahimi, Ali Ghorbanpour, Soroush Sadeghian, Sara Salamat, Muhan Li, Hai Son Le, Mahdi Bashari and Ebrahim Bagheri)
Safeguarding Generative AI Applications in Preclinical Imaging through Hybrid Anomaly Detection (Jakub Binda, Valentina Paneta, Vassilis Eleftheriadis, Hongkyou Chung, Panagiotis Papadimitroulas and Neo Christopher Chung)
Taming the Unicorn: Turning Generative AI Into a Workhorse — How to Draw Boundaries, Handle Hallucinations, and Make AI Behave in Product (Marios Kokkodis, Purusoth Mahendran and Grace Boatwright)
Industry Day 4: LLM Applications in E-commerce and Ads
Using Large Language Models to Improve Product Information in E-commerce Catalogs (Gang Luo, Julien Han, Hayreddin Ceker and Karim Bouyarmane)
LLM-Driven Attributes Extraction in eCommerce (Ksenia Riabinova and Kilian Merkelbach)
ROI Scan: LLM-powered Object-level Similarity Search for Google Ads Content Moderation (Enming Luo, Yintao Liu, Dongjin Kwon, Rich Munoz, Wei Qiao, Nic Trieu, Eric Xiao, Jimin Li, Laurel Graham and Ariel Fuxman)
Google Ads Content Moderation with RAG (Yuan Wang, Wei Qiao, Jingxiang Li, Tiantian Fang, Eric Xiao, Yi-Ting Chen, Zhongli Ding, Enming Luo, Megan Oftelie, Zhimin Wang, Yintao Liu and Jimin Li)