1 citations · 1 across the 4 of their papers we have counts for
4 papers
Structure-aware Relative Policy Optimization for Ranking
Yiteng Tu, Weihang Su, Zitao Su +3
Ranking is a fundamental component of modern information access systems. Reinforcement learning (RL) provides a flexible framework for directly optimizing coarse-grained feedback a…
Generative Chinese Statute Retrieval
Yiteng Tu, Zitao Su, Weihang Su +5
Statute retrieval is a fundamental task in legal information retrieval, yet existing approaches struggle to bridge the gap between colloquial legal queries and formal statutory lan…
Generalized Pseudo-Relevance Feedback
Yiteng Tu, Weihang Su, Yujia Zhou +4
Query rewriting is a fundamental technique in information retrieval (IR). It typically employs the retrieval result as relevance feedback to refine the query and thereby addresses…
Reinforcement Learning to Rank Using Coarse-grained Rewards
Yiteng Tu, Zhichao Xu, Tao Yang +6
Learning to rank (LTR) plays a crucial role in various Information Retrieval (IR) tasks. Although supervised LTR methods based on fine-grained relevance labels (e.g., document-leve…