3 papers
cs.IR2026
Decoupled Residual Quantization for Robust Semantic IDs in Recommendation
Xuesi Wang, Junjie Wang, Ziliang Wang +2
Semantic IDs represent items as shared discrete token sequences and have become a practical tool for recommendation and retrieval. Yet it remains difficult to tell why a tokenizer…
cs.IR2026
UniRec: Bridging the Expressive Gap between Generative and Discriminative Recommendation via Chain-of-Attribute
Ziliang Wang, Gaoyun Lin, Xuesi Wang +7
Generative Recommendation (GR) reframes retrieval and ranking as autoregressive decoding over Semantic IDs (SIDs), unifying the multi-stage pipeline into a single model. Yet a fund…
cs.AI2025
Establishing Reliability Metrics for Reward Models in Large Language Models
Yizhou Chen, Yawen Liu, Xuesi Wang +5
The reward model (RM) that represents human preferences plays a crucial role in optimizing the outputs of large language models (LLMs), e.g., through reinforcement learning from hu…