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Ryo Hachiuma

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#artificial intelligence Preprint Sep 2026

Mid-Harness: Scaling Actions Between Model and Harness for Terminal Agents

Terminal agents act through stochastic model generations, yet the ability to generate a useful action does not ensure its reliable execution. A poor command (e.g., wrong package install) can change the environment in ways that hinder subsequent progress, even when the model could generate a better alternative. We inves...

Minki Kang, Ryo Hachiuma, Shao-Kun Zhang et al. · 0 citations
Preprint Aug 2026

Guardrail-Agnostic Societal Bias Evaluation in Large Vision-Language Models

A societal bias evaluation method for large vision-language models (LVLMs) in the era of strong safety guardrails is proposed, finding that all models undesirably use user demographic information in person-irrelevant tasks.

Yusuke Hirota, Michael Boone, Arun George Zachariah et al. · 0 citations

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