All Stories

  1. Bursting Filter Bubble: Enhancing Serendipity Recommendations with Aligned Large Language Models
  2. Action First: Leveraging Preference-Aware Actions for More Effective Decision-Making in Interactive Recommender Systems
  3. Efficiency Unleashed: Inference Acceleration for LLM-based Recommender Systems with Speculative Decoding
  4. Efficient and Deployable Knowledge Infusion for Open-World Recommendations via Large Language Models
  5. MemoCRS: Memory-enhanced Sequential Conversational Recommender Systems with Large Language Models
  6. Towards Open-World Recommendation with Knowledge Augmentation from Large Language Models
  7. DisCo: Towards Harmonious Disentanglement and Collaboration between Tabular and Semantic Space for Recommendation
  8. How Can Recommender Systems Benefit from Large Language Models: A Survey
  9. Utility-oriented Reranking with Counterfactual Context
  10. ClickPrompt: CTR Models are Strong Prompt Generators for Adapting Language Models to CTR Prediction
  11. A Bird's-eye View of Reranking: From List Level to Page Level
  12. Multi-Level Interaction Reranking with User Behavior History
  13. U-rank