All Stories

  1. Tapping the Potential of Large Language Models as Recommender Systems: A Comprehensive Framework and Empirical Analysis
  2. Sequence-level Semantic Representation Fusion for Recommender Systems
  3. Promoting Two-sided Fairness with Adaptive Weights for Providers and Customers in Recommendation
  4. Towards a More User-Friendly and Easy-to-Use Benchmark Library for Recommender Systems