Shih-Han Chou — accepted AI-conference papers

2025

MM-R3: On (In-)Consistency of Vision-Language Models (VLMs)

Shih-Han Chou, Shivam Chandhok, Jim Little, Leonid Sigal

ACL 2025finding

With the advent of LLMs and variants, a flurry of research has emerged, analyzing the performance of such models across an array of tasks. While most studies focus on evaluating the capabilities of state-of-the-art (SoTA) Vision Language Models (VLMs) through task accuracy (e.g., visual question ans…

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2017

Agent-Centric Risk Assessment: Accident Anticipation and Risky Region Localization

Kuo-Hao Zeng, Shih-Han Chou, Fu-Hsiang Chan, Juan Carlos Niebles, Min Sun

CVPR 2017spotlight

For survival, a living agent (e.g., human in Fig. 1(a)) must have the ability to assess risk (1) by temporally anticipating accidents before they occur (Fig. 1(b)), and (2) by spatially localizing risky regions (Fig. 1(c)) in the environment to move away from threats. In this paper, we take an agent…

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