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20242026
most citedSafeAgentBench: A Benchmark for Safe Task Planning of Embodied LLM Agents

2 citations · 2 across the 9 of their papers we have counts for

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cs.CL2026

MASLab: A Unified and Comprehensive Codebase for LLM-based Multi-Agent Systems

Rui Ye, Keduan Huang, Qimin Wu +17

LLM-based multi-agent systems (MAS) have demonstrated significant potential in enhancing single LLMs to address complex and diverse tasks in practical applications. Despite conside…

cs.CL2026

HyperTool: Beyond Step-Wise Tool Calls for Tool-Augmented Agents

Yaxin Du, Yifan Zhou, Yujie Ge +7

Tool-augmented LLM agents commonly rely on step-wise atomic tool calls, where each invocation, observation, and value transfer is exposed in the main reasoning trace. This creates…

cs.CL2025

InfoMosaic-Bench: Evaluating Multi-Source Information Seeking in Tool-Augmented Agents

Yaxin Du, Yuanshuo Zhang, Xiyuan Yang +10

Information seeking is a fundamental requirement for humans. However, existing LLM agents rely heavily on open-web search, which exposes two fundamental weaknesses: online content…

cs.CL2024

Are We There Yet? Revealing the Risks of Utilizing Large Language Models in Scholarly Peer Review

Rui Ye, Xianghe Pang, Jingyi Chai +6

Scholarly peer review is a cornerstone of scientific advancement, but the system is under strain due to increasing manuscript submissions and the labor-intensive nature of the proc…

cs.CL2024

Self-Alignment of Large Language Models via Monopolylogue-based Social Scene Simulation

Xianghe Pang, Shuo Tang, Rui Ye +4

Aligning large language models (LLMs) with human values is imperative to mitigate potential adverse effects resulting from their misuse. Drawing from the sociological insight that…