arXiv Computer Vision August 26, 2026 By Junlong Li, Junxi Li, Jianjun Gao, Chen Cai, Lap-Pui Chau, Yi Wang

EgoErrorVQA: Assess Egocentric Comprehension Capabilities through Procedural Errors for Ego-Agentic AI

Read the original on arXiv Computer Vision →

EgoErrorVQA introduces a new egocentric visual question answering task that evaluates visual agents’ ability to detect procedural errors in everyday activities. The paper presents an evaluator agent built on the Agent2Agent protocol and shows that current models struggle with procedural error recognition. It also proposes Ego-ADR, an Adaptive Decoupled Reasoning framework that improves performance on the task, achieving state‑of‑the‑art results.

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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