All Stories

  1. SurGE: A Benchmark and Evaluation Framework for Scientific Survey Generation
  2. Corrigendum: A Content- and Context-Aware Click Model Based on Dynamic Graph Neural Networks
  3. A Content- and Context-Aware Click Model Based on Dynamic Graph Neural Networks
  4. The Effect of Task Complexity and Domain Expertise on Search Performance and User Behavior in Conversational Exploratory Search
  5. How do Large Language Models Understand Relevance? A Mechanistic Interpretability Perspective
  6. Adapting LLMs for Personalized Evaluation of Explanations for Recommendations: A Meta-Learning Approach based on MAML
  7. Addressing Personalized Bias for Unbiased Learning to Rank
  8. Dense Retrieval for Aggregated Search
  9. CLUE: Using Large Language Models for Judging Document Usefulness in Web Search Evaluation
  10. FinS-Pilot: A Benchmark for Online Financial RAG System
  11. MGIPF: Multi-Granularity Interest Prediction Framework for Personalized Recommendation
  12. Distributionally Robust Optimization for Unbiased Learning to Rank
  13. Exploring Human-Like Thinking in Search Simulations with Large Language Models
  14. A Flexible User Study Platform for Generative Information Retrieval
  15. Investigating the Robustness of Counterfactual Learning to Rank Models: A Reproducibility Study
  16. Leveraging Passage Embeddings for Efficient Listwise Reranking with Large Language Models
  17. TourRank: Utilizing Large Language Models for Documents Ranking with a Tournament-Inspired Strategy
  18. MA4DIV: Multi-Agent Reinforcement Learning for Search Result Diversification
  19. Investigating Users' Search Behavior and Outcome with ChatGPT in Learning-oriented Search Tasks
  20. Mamba Retriever: Utilizing Mamba for Effective and Efficient Dense Retrieval
  21. Aligning Explanations for Recommendation with Rating and Feature via Maximizing Mutual Information
  22. Scaling Laws For Dense Retrieval
  23. USimAgent: Large Language Models for Simulating Search Users
  24. An Integrated Data Processing Framework for Pretraining Foundation Models
  25. CoSearchAgent: A Lightweight Collaborative Search Agent with Large Language Models
  26. An Analysis on Matching Mechanisms and Token Pruning for Late-interaction Models
  27. An Intent Taxonomy of Legal Case Retrieval
  28. Improving First-stage Retrieval of Point-of-Interest Search by Pre-training Models
  29. Understanding the Multi-vector Dense Retrieval Models
  30. Constructing Tree-based Index for Efficient and Effective Dense Retrieval
  31. Session Search with Pre-trained Graph Classification Model
  32. A Passage-Level Reading Behavior Model for Mobile Search
  33. User Behavior Simulation for Search Result Re-ranking
  34. Understanding Relevance Judgments in Legal Case Retrieval
  35. Evaluating Interpolation and Extrapolation Performance of Neural Retrieval Models
  36. 4th Workshop on Deep Learning Practice and Theory for High-Dimensional Sparse and Imbalanced Data with KDD 2022
  37. Axiomatically Regularized Pre-training for Ad hoc Search
  38. Webformer
  39. Generating Clarifying Questions with Web Search Results
  40. Learning Probabilistic Box Embeddings for Effective and Efficient Ranking
  41. Global or Local: Constructing Personalized Click Models for Web Search
  42. A Cooperative Neural Information Retrieval Pipeline with Knowledge Enhanced Automatic Query Reformulation
  43. Learning Discrete Representations via Constrained Clustering for Effective and Efficient Dense Retrieval
  44. Jointly Optimizing Query Encoder and Product Quantization to Improve Retrieval Performance
  45. POSSCORE
  46. Incorporating Query Reformulating Behavior into Web Search Evaluation
  47. Evaluating Relevance Judgments with Pairwise Discriminative Power
  48. A Hybrid Framework for Session Context Modeling
  49. Optimizing Dense Retrieval Model Training with Hard Negatives
  50. Investigating User Behavior in Legal Case Retrieval
  51. Investigating Session Search Behavior with Knowledge Graphs
  52. Unbiased Learning to Rank
  53. Constructing a Comparison-based Click Model for Web Search
  54. Towards a Better Understanding of Query Reformulation Behavior in Web Search
  55. Topic-enhanced knowledge-aware retrieval model for diverse relevance estimation
  56. Challenges in designing a brain-machine search interface
  57. Neural Logic Reasoning
  58. Learning Better Representations for Neural Information Retrieval with Graph Information
  59. Preference-based Evaluation Metrics for Web Image Search
  60. Models Versus Satisfaction
  61. Cascade or Recency
  62. Investigating Reading Behavior in Fine-grained Relevance Judgment
  63. An Analysis of BERT in Document Ranking
  64. Modeling User Behavior for Vertical Search: Images, Apps and Products
  65. Leveraging Passage-level Cumulative Gain for Document Ranking
  66. "Revisiting information retrieval tasks with user behavior models" by Yiqun Liu and Jiaxin Mao with Martin Vesely as coordinator
  67. TianGong-ST
  68. Improving Web Image Search with Contextual Information
  69. Investigating the Learning Process in Job Search
  70. Context-Aware Ranking by Constructing a Virtual Environment for Reinforcement Learning
  71. Investigating the Reliability of Click Models
  72. Search Result Reranking with Visual and Structure Information Sources
  73. Teach Machine How to Read
  74. Towards Context-Aware Evaluation for Image Search
  75. Investigating Passage-level Relevance and Its Role in Document-level Relevance Judgment
  76. Human Behavior Inspired Machine Reading Comprehension
  77. SIGIR 2019 Tutorial on Explainable Recommendation and Search
  78. WWW’19 Tutorial on Explainable Recommendation and Search
  79. Grid-based Evaluation Metrics for Web Image Search
  80. Understanding Reading Attention Distribution during Relevance Judgement
  81. Unbiased Learning to Rank
  82. How Does Domain Expertise Affect Users’ Search Interaction and Outcome in Exploratory Search?
  83. Constructing Click Models for Mobile Search
  84. Towards Designing Better Session Search Evaluation Metrics
  85. ACM SIGIR Student Liaison Program
  86. "Satisfaction with Failure" or "Unsatisfied Success"
  87. Understanding and Predicting Usefulness Judgment in Web Search
  88. When does Relevance Mean Usefulness and User Satisfaction in Web Search?