3 papers
cs.AI2025
Proof-of-Use: Mitigating Tool-Call Hacking in Deep Research Agents
SHengjie Ma, Chenlong Deng, Jiaxin Mao +5
While reinforcement learning (RL) enhances their ability to plan and reason across retrieval steps, we identify a critical failure mode in this setting: Tool-Call Hacking. Unlike e…
cs.CL2024
Think-on-Graph 2.0: Deep and Faithful Large Language Model Reasoning with Knowledge-guided Retrieval Augmented Generation
Shengjie Ma, Chengjin Xu, Xuhui Jiang +5
Retrieval-augmented generation (RAG) has improved large language models (LLMs) by using knowledge retrieval to overcome knowledge deficiencies. However, current RAG methods often f…
cs.AI2024
Leveraging Large Language Models for Relevance Judgments in Legal Case Retrieval
Shengjie Ma, Qi Chu, Jiaxin Mao +3
Determining which legal cases are relevant to a given query involves navigating lengthy texts and applying nuanced legal reasoning. Traditionally, this task has demanded significan…