1 citations · 1 across the 8 of their papers we have counts for
4 papers · 1 filter
MLLMs Fail to Refuse when Using Tools Agentically
Rikiya Takehi, Ryo Hachiuma, Shaona Ghosh +3
Agentic multimodal large language models (MLLMs) have recently pushed the frontier of visual reasoning by calling tools such as zooming and tagging. Despite the recent strong succe…
Guardrail-Agnostic Societal Bias Evaluation in Large Vision-Language Models
Yusuke Hirota, Michael Ross Boone, Arun George Zachariah +4
We propose a societal bias evaluation method for large vision-language models (LVLMs) in the era of strong safety guardrails. Existing benchmarks rely on prompts that ask models to…
VIBE: Voice-Induced open-ended Bias Evaluation for Large Audio-Language Models via Real-World Speech
Yi-Cheng Lin, Yusuke Hirota, Sung-Feng Huang +1
Large Audio-Language Models (LALMs) are increasingly integrated into daily applications, yet their generative biases remain underexplored. Existing speech fairness benchmarks rely…
Interpretable Debiasing of Vision-Language Models for Social Fairness
Na Min An, Yoonna Jang, Yusuke Hirota +3
The rapid advancement of Vision-Language models (VLMs) has raised growing concerns that their black-box reasoning processes could lead to unintended forms of social bias. Current d…