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20242026
most citedCaution for the Environment: Multimodal LLM Agents are Susceptible to Environmental Distractions

1 citations · 1 across the 12 of their papers we have counts for

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cs.CL2026

StyleBench: Evaluating Speech Language Models on Conversational Speaking Style Control

Haishu Zhao, Aokai Hao, Yuan Ge +3

Speech language models (SLMs) have significantly extended the interactive capability of text-based Large Language Models (LLMs) by incorporating paralinguistic information. For mor…

cs.CL2025

How Deep is Love in LLMs' Hearts? Exploring Semantic Size in Human-like Cognition

Yao Yao, Yifei Yang, Xinbei Ma +4

How human cognitive abilities are formed has long captivated researchers. However, a significant challenge lies in developing meaningful methods to measure these complex processes.…

cs.CL2025

Textual-to-Visual Iterative Self-Verification for Slide Generation

Yunqing Xu, Xinbei Ma, Jiyang Qiu +1

Generating presentation slides is a time-consuming task that urgently requires automation. Due to their limited flexibility and lack of automated refinement mechanisms, existing au…

cs.CL2024

MEGen: Generative Backdoor into Large Language Models via Model Editing

Jiyang Qiu, Xinbei Ma, Zhuosheng Zhang +3

Large language models (LLMs) have exhibited remarkable versatility and adaptability, while their widespread adoption across various applications also raises critical safety concern…

cs.CL2024★ 1 cited

Caution for the Environment: Multimodal LLM Agents are Susceptible to Environmental Distractions

Xinbei Ma, Yiting Wang, Yao Yao +4

This paper investigates the faithfulness of multimodal large language model (MLLM) agents in a graphical user interface (GUI) environment, aiming to address the research question o…

cs.CL2024

On the Robustness of Editing Large Language Models

Xinbei Ma, Tianjie Ju, Jiyang Qiu +4

Large language models (LLMs) have played a pivotal role in building communicative AI, yet they encounter the challenge of efficient updates. Model editing enables the manipulation…