Abstract is missing.
- A Comparative Study of Training Objectives for Clarification Facet GenerationShiyu Ni, Keping Bi, Jiafeng Guo, Xueqi Cheng. 1-10 [doi]
- Retrieving Supporting Evidence for Generative Question AnsweringSiqing Huo, Negar Arabzadeh, Charles L. A. Clarke. 11-20 [doi]
- Recommending Answers to Math Questions Based on KL-Divergence and Approximate XML Tree MatchingSiqi Gao, Yiu-Kai Dennis Ng. 21-31 [doi]
- EALM: Introducing Multidimensional Ethical Alignment in Conversational Information RetrievalYiyao Yu, Junjie Wang, Yuxiang Zhang, Lin Zhang, Yujiu Yang, Tetsuya Sakai. 32-39 [doi]
- Open-Domain Dialogue Quality Evaluation: Deriving Nugget-level Scores from Turn-level ScoresRikiya Takehi, Akihisa Watanabe, Tetsuya Sakai. 40-45 [doi]
- ChatGPT Hallucinates when Attributing AnswersGuido Zuccon, Bevan Koopman, Razia Shaik. 46-51 [doi]
- Multimodal Fashion Knowledge Extraction as CaptioningYifei Yuan 0002, Wenxuan Zhang, Yang Deng 0002, Wai Lam. 52-62 [doi]
- Chuweb21D: A Deduped English Document Collection for Web Search TasksZhumin Chu, Tetsuya Sakai, Qingyao Ai, Yiqun Liu 0001. 63-72 [doi]
- Generating Natural Language Queries for More Effective Systematic Review Screening PrioritisationShuai Wang, Harrisen Scells, Bevan Koopman, Martin Potthast, Guido Zuccon. 73-83 [doi]
- Examination of Information Problem Decomposition Strategies: A New Perspective for Understanding Users' Information Problems in Search as LearningXiaoyue Zhang, Chang Liu. 84-94 [doi]
- ReviVal: Towards Automatically Evaluating the Informativeness of Peer ReviewsRajeev Verma, Tirthankar Ghosal, Saprativa Bhattacharjee, Asif Ekbal, Pushpak Bhattacharyya. 95-103 [doi]
- User-Meal Interaction Learning for Meal Recommendation: A Reproducibility StudyMing Li, Lin Li, Xiaohui Tao, Ning Zhong 0001. 104-113 [doi]
- RFR: Representation-Focused Replay for Overcoming the Catastrophic Forgetting in Lifelong Language LearningZhongyuan Han, Zeyang Peng, Leilei Kong, Zhanhong Ye, Mingjie Huang, Haoliang Qi. 114-121 [doi]
- Towards Sequential Counterfactual Learning to RankTesi Xiao, Branislav Kveton, Sumeet Katariya, Tanmay Gangwani, Anshuka Rangi. 122-128 [doi]
- Unbiased Top-$k$ Learning to Rank with Causal Likelihood DecompositionHaiyuan Zhao, Jun Xu, Xiao Zhang, Guohao Cai, Zhenhua Dong, Ji-Rong Wen. 129-138 [doi]
- Annotating Data for Fine-Tuning a Neural Ranker? Current Active Learning Strategies are not Better than Random SelectionSophia Althammer, Guido Zuccon, Sebastian Hofstätter, Suzan Verberne, Allan Hanbury. 139-149 [doi]
- Enhancing Sparse Retrieval via Unsupervised LearningXueguang Ma, Hengxin Fun, Xusen Yin, Antonio Mallia, Jimmy Lin. 150-157 [doi]
- Result Diversification for Legal case RetrievalRuizhe Zhang 0005, Qingyao Ai, Yueyue Wu, Yixiao Ma, Yiqun Liu 0001. 158-168 [doi]
- Investigating the Influence of Legal Case Retrieval Systems on Users' Decision ProcessBeining Wang, Ruizhe Zhang 0005, Yueyue Wu, Qingyao Ai, Min Zhang, Yiqun Liu 0001. 169-175 [doi]
- Boosting legal case retrieval by query content selection with large language modelsYouchao Zhou, Heyan Huang, Zhijing Wu 0001. 176-184 [doi]
- Lossy Compression Options for Dense Index RetentionJoel Mackenzie, Alistair Moffat. 185-194 [doi]
- How to Index Item IDs for Recommendation Foundation ModelsWenyue Hua, Shuyuan Xu, Yingqiang Ge, Yongfeng Zhang. 195-204 [doi]
- Adaptive Learning on User Segmentation: Universal to Specific Representation via Bipartite Neural InteractionXiaoyu Tan, Yongxin Deng, Chao Qu, Siqiao Xue, Xiaoming Shi, James Zhang, Xihe Qiu. 205-211 [doi]
- Typos-aware Bottlenecked Pre-Training for Robust Dense RetrievalShengyao Zhuang, Linjun Shou, Jian Pei, Ming Gong, Houxing Ren, Guido Zuccon, Daxin Jiang. 212-222 [doi]
- Selecting which Dense Retriever to use for Zero-Shot SearchEkaterina Khramtsova, Shengyao Zhuang, Mahsa Baktashmotlagh, Xi Wang, Guido Zuccon. 223-233 [doi]
- Vertical Allocation-based Fair Exposure Amortizing in RankingTao Yang 0030, Zhichao Xu, Qingyao Ai. 234-244 [doi]
- Automatic Feature Fairness in Recommendation via AdversariesHengchang Hu, Yiming Cao, Zhankui He, Samson Tan, Min-Yen Kan. 245-252 [doi]
- Sequential Recommendation with User Evolving Preference DecompositionWeiqi Shao, Xu Chen, Jiashu Zhao, Long Xia, Jingsen Zhang, Dawei Yin. 253-263 [doi]
- Multi-Behavior Job Recommendation with Dynamic AvailabilityYosuke Saito, Kazunari Sugiyama. 264-271 [doi]
- AdaReX: Cross-Domain, Adaptive, and Explainable Recommender SystemYi Yu, Kazunari Sugiyama, Adam Jatowt. 272-281 [doi]
- Reinforcement Re-ranking with 2D Grid-based Recommendation PanelsSirui Chen, Xiao Zhang, Xu Chen, Zhiyu Li, Yuan Wang, Quan Lin, Jun Xu. 282-287 [doi]
- SE-PEF: a Resource for Personalized Expert FindingPranav Kasela, Gabriella Pasi, Raffaele Perego 0001. 288-309 [doi]
- Recent Advances in Generative Information RetrievalYubao Tang, Ruqing Zhang 0001, Jiafeng Guo, Maarten de Rijke. 294-297 [doi]
- Rethinking Conversational Agents in the Era of LLMs: Proactivity, Non-collaborativity, and BeyondYang Deng, Wenqiang Lei, Minlie Huang, Tat-Seng Chua. 298-301 [doi]
- Rethinking Conversational Agents in the Era of LLMs: Proactivity, Non-collaborativity, and BeyondKrisztian Balog, ChengXiang Zhai. 302-305 [doi]
- Large Language Models for Recommendation: Progresses and Future DirectionsKeqin Bao, Jizhi Zhang, Yang Zhang, Wang Wenjie, Fuli Feng, Xiangnan He 0001. 306-309 [doi]