From the 1 of 33 linked papers with an AI index.
33 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…
Co-Evolving LLM Evaluators and Policies via DynamicRubric
Beining Wang, Weihang Su, Hongtao Tian +8
Post-training with evaluator feedback on policy-induced samples serves as a major mechanism for improving large language models. As policies improve, these sampled responses become…
Generative Chinese Statute Retrieval
Yiteng Tu, Zitao Su, Weihang Su +5
The paper introduces GCSR, a generative framework that treats Chinese statute retrieval as a sequence generation task and embeds hierarchical legal knowledge into the model to impr…
RWGBench: Evaluating Scholarly Positioning in Related Work Generation
Anzhe Xie, Weihang Su, Jiaxin Mao +4
Large language models have shown strong fluency in scientific writing, yet the evaluation of related work generation (RWG) remains limited. Existing RWG evaluations largely inherit…
MetaSyn: A Benchmark for LLM Agents on Meta-Analysis Articles from Nature Portfolio
Anzhe Xie, Weihang Su, Yujia Zhou +3
Systematic review and meta-analysis is an important method for scientific research. It comprehensively studies target research questions by combining evidence from multiple indepen…
Improve Large Language Model Systems with User Logs
Changyue Wang, Weihang Su, Qingyao Ai +4
Scaling training data and model parameters has long driven progress in large language models (LLMs), but this paradigm is increasingly constrained by the scarcity of high-quality d…