D&A: Decoupling Description and Assessment Enables VLMs as Zero-Shot Robotic Reward Models
Paper recorded by Signals 4 on 2026-11-02 in cs.AI. Abstract reproduced from arXiv; link to the original below.
Published 2026-11-02 on arXiv · recorded by Signals 4 on 2026-11-03
Category: cs.AI · 人工智能 · first seen 2026-11-03
Abstract
Vision-Language Models (VLMs) hold promise for zero-shot video task-progress estimation in robot learning, yet existing frameworks frequently suffer from confirmation bias, hallucinating progress in failed executions due to implicit success assumptions or relative temporal ranking designs. Naive prompting of frontier models collapses into a binary success detector that fails to capture nuanced, no
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