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20232026
most citedEvil Geniuses: Delving into the Safety of LLM-based Agents

6 citations · 9 across the 21 of their papers we have counts for

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5 papers · 1 filter

cs.CL2026

Reasoning as State Transition: A Representational Analysis of Reasoning Evolution in Large Language Models

Siyuan Zhang, Jialian Li, Yichi Zhang +3

Large Language Models have achieved remarkable performance on reasoning tasks, motivating research into how this ability evolves during training. Prior work has primarily analyzed…

cs.CL2025

Unveiling Trust in Multimodal Large Language Models: Evaluation, Analysis, and Mitigation

Yichi Zhang, Yao Huang, Yifan Wang +10

The trustworthiness of Multimodal Large Language Models (MLLMs) remains an intense concern despite the significant progress in their capabilities. Existing evaluation and mitigatio…

cs.CL2025

Exploring the Generalizability of Factual Hallucination Mitigation via Enhancing Precise Knowledge Utilization

Siyuan Zhang, Yichi Zhang, Yinpeng Dong +1

Large Language Models (LLMs) often struggle to align their responses with objective facts, resulting in the issue of factual hallucinations, which can be difficult to detect and mi…

cs.CL2024

MultiTrust: A Comprehensive Benchmark Towards Trustworthy Multimodal Large Language Models

Yichi Zhang, Yao Huang, Yitong Sun +10

Despite the superior capabilities of Multimodal Large Language Models (MLLMs) across diverse tasks, they still face significant trustworthiness challenges. Yet, current literature…

cs.CL2023★ 6 cited

Evil Geniuses: Delving into the Safety of LLM-based Agents

Yu Tian, Xiao Yang, Jingyuan Zhang +2

Rapid advancements in large language models (LLMs) have revitalized in LLM-based agents, exhibiting impressive human-like behaviors and cooperative capabilities in various scenario…