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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…
Memory-Aware and Uncertainty-Guided Retrieval for Multi-Hop Question Answering
Yuelyu Ji, Rui Meng, Zhuochun Li +1
Multi-hop question answering (QA) requires models to retrieve and reason over multiple pieces of evidence. While Retrieval-Augmented Generation (RAG) has made progress in this area…
Benchmarking LLMs for Political Science: A United Nations Perspective
Yueqing Liang, Liangwei Yang, Chen Wang +6
Large Language Models (LLMs) have achieved significant advances in natural language processing, yet their potential for high-stake political decision-making remains largely unexplo…