All Stories

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