1 citations · 1 across the 7 of their papers we have counts for
8 papers
Turn-PPO: Turn-Level Advantage Estimation with PPO for Improved Multi-Turn RL in Agentic LLMs
Junbo Li, Peng Zhou, Rui Meng +3
Reinforcement learning (RL) has re-emerged as a natural approach for training interactive LLM agents in real-world environments. However, directly applying the widely used Group Re…
Retrieval--Reasoning Processes for Multi-hop Question Answering: A Four-Axis Design Framework and Empirical Trends
Yuelyu Ji, Zhuochun Li, Rui Meng +1
Multi-hop question answering (QA) requires systems to iteratively retrieve evidence and reason across multiple hops. While recent RAG and agentic methods report strong results, the…
Harnessing Deep LLM Participation for Robust Entity Linking
Jiajun Hou, Chenyu Zhang, Rui Meng
Entity Linking (EL), the task of mapping textual entity mentions to their corresponding entries in knowledge bases, constitutes a fundamental component of natural language understa…
Weakly Supervised Medical Entity Extraction and Linking for Chief Complaints
Zhimeng Luo, Zhendong Wang, Rui Meng +3
A Chief complaint (CC) is the reason for the medical visit as stated in the patient's own words. It helps medical professionals to quickly understand a patient's situation, and als…
Universal Retrieval for Multimodal Trajectory Modeling
Xuan Zhang, Ziyan Jiang, Rui Meng +5
Trajectory data, capturing human actions and environmental states across various modalities, holds significant potential for enhancing AI agent capabilities, particularly in GUI en…
Curriculum Guided Reinforcement Learning for Efficient Multi Hop Retrieval Augmented Generation
Yuelyu Ji, Rui Meng, Zhuochun Li +1
Retrieval-augmented generation (RAG) grounds large language models (LLMs) in up-to-date external evidence, yet existing multi-hop RAG pipelines still issue redundant subqueries, ex…