Shishen Gu — accepted AI-conference papers

2026

Benchmarking Trustworthiness in Multimodal LLMs for Video Understanding

Youze Wang, Zijun Chen, Ruoyu Chen, Shishen Gu, Wenbo Hu, Jiayang Liu +5

AAAI 2026technical

Recent advancements in multimodal large language models for video understanding (videoLLMs) have enhanced their capacity to process complex spatiotemporal data. However, challenges such as factual inaccuracies, harmful content, biases, hallucinations, and privacy risks compromise their reliability.

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2025

SURE: Safety Understanding and Reasoning Enhancement for Multimodal Large Language Models

Yuxin Gou, Xiaoning Dong, Qin Li, Shishen Gu, Richang Hong, Wenbo Hu

EMNLP 2025

Multimodal large language models (MLLMs) demonstrate impressive capabilities by integrating visual and textual information. However, the incorporation of visual modalities also introduces new and complex safety risks, rendering even the most advanced models vulnerable to sophisticated jailbreak atta

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