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arXiv Computer Vision By Chanseul Cho, Jaesung Jun, Dongheon Lee, Youngmin Ro

Attention Maps Know When to Think: Training-Free Difficulty-Aware Chain-of-Thought for Reasoning Segmentation

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The paper introduces Difficulty-Aware Chain-of-Thought (DA‑CoT), a training‑free framework that selectively applies chain‑of‑thought prompting in reasoning segmentation tasks based on the entropy of attention maps. Low entropy signals confident, localized grounding, while high entropy indicates uncertainty and the potential benefit of additional reasoning. DA‑CoT also incorporates a Bidirectional Rethinking mechanism to automatically reverse reasoning decisions when initial outputs fail, thereby improving robustness and inference efficiency while achieving state‑of‑the‑art results on Reasoning Segmentation benchmarks.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Computer Vision.

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