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Looks the Same, Answers Differently: Flip-Direction Steering for Robust Vision-Language Reasoning

arXiv:2609.28851v1 Announce Type: new Abstract: Vision-language models (VLMs) achieve strong visual reasoning performance, yet subtle changes from routine image capture and processing can alter their reasoning trajectories even when images appear nearly identical. In long-horizon generation, the re…

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  1. 2026-09-25 04:00 · arXiv cs.CV
    Looks the Same, Answers Differently: Flip-Direction Steering for Robust Vision-Language Reasoning

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