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Xin Xin

Shandong University, Information Retrieval Lab, School of Computer Science and Technology, China

23 papers at tracked venues · 15 at CORE A* · active 20242026

Venues

Frequent coauthors

Papers

  1. MCoT-MVS: Multi-level Vision Selection by Multi-modal Chain-of-Thought Reasoning for Composed Image Retrieval
  2. R2NS: Recall and Re-ranking of Negative Samples for Sequential Recommendation
  3. Reinforced Efficient Reasoning via Semantically Diverse Exploration
  4. AgentIR: 2nd Workshop on Agent-based Information Retrieval
  5. Exploration and Exploitation of Hard Negative Samples for Cross-Domain Sequential Recommendation
  6. How Does Topology Bias Distort Message Passing in Graph Recommender? A Dirichlet Energy Perspective
  7. Improving Sequential Recommenders through Counterfactual Augmentation of System Exposure
  8. Measuring Interaction-Level Unlearning Difficulty for Collaborative Filtering
  9. Offline Trajectory Optimization for Offline Reinforcement Learning
  10. OmniKV: Dynamic Context Selection for Efficient Long-Context LLMs
  11. Reidentify: Context-Aware Identity Generation for Contextual Multi-Agent Reinforcement Learning
  12. The 1st EReL@MIR Workshop on Efficient Representation Learning for Multimodal Information Retrieval
  13. Towards Personalized Federated Multi-Scenario Multi-Task Recommendation
  14. AgentIR: 1st Workshop on Agent-based Information Retrieval
  15. Confucius: Iterative Tool Learning from Introspection Feedback by Easy-to-Difficult Curriculum
  16. Content-Based Collaborative Generation for Recommender Systems
  17. Debiasing Sequential Recommenders through Distributionally Robust Optimization over System Exposure
  18. IISAN: Efficiently Adapting Multimodal Representation for Sequential Recommendation with Decoupled PEFT
  19. MEFT: Memory-Efficient Fine-Tuning through Sparse Adapter
  20. On the Effectiveness of Unlearning in Session-Based Recommendation
    WSDM 2024 · Xin Xin
  21. PSL: Rethinking and Improving Softmax Loss from Pairwise Perspective for Recommendation
  22. Sparks of Surprise: Multi-objective Recommendations with Hierarchical Decision Transformers for Diversity, Novelty, and Serendipity
  23. Towards Empathetic Conversational Recommender Systems