All Stories

  1. MemoCRS: Memory-enhanced Sequential Conversational Recommender Systems with Large Language Models
  2. Towards Open-World Recommendation with Knowledge Augmentation from Large Language Models
  3. DisCo: Towards Harmonious Disentanglement and Collaboration between Tabular and Semantic Space for Recommendation
  4. How Can Recommender Systems Benefit from Large Language Models: A Survey
  5. Utility-oriented Reranking with Counterfactual Context
  6. ClickPrompt: CTR Models are Strong Prompt Generators for Adapting Language Models to CTR Prediction
  7. A Bird's-eye View of Reranking: From List Level to Page Level
  8. Multi-Level Interaction Reranking with User Behavior History
  9. U-rank