Divergence Meets Consensus: A Multi-Source Negative Sampling Framework for Sequential Recommendation

Negative sampling is significant for training sequential recommendation models under implicit feedback. The predominant strategy, self-guided hard negative sampling, selects negatives based on the model's current state but suffers from three limitations: (1) the coupling between sampling and model u...