Diagnosing the Sources of Compositional Failure in Vision-Language Models: A Controlled Analysis
Paper recorded by Signals 4 on 2026-09-25 in cs.CV. Abstract reproduced from arXiv; link to the original below.
Published 2026-09-25 on arXiv · recorded by Signals 4 on 2026-09-28
Category: cs.CV · 计算机视觉 · first seen 2026-09-28
Abstract
Vision-language models (VLMs) often struggle with compositional reasoning tasks, but the reasons for this underperformance remain unclear. A common hypothesis is that models struggle to integrate multiple components, leading to training interventions to improve compositional binding. However, this assumption has never been directly quantified. Existing benchmarks evaluate captions only in their co
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Cite this page: Diagnosing the Sources of Compositional Failure in Vision-Language Models: A Controlled Analysis: the #25 most recent of 342 cs.CV papers we have recorded (as of 2026-09-25). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/diagnosing-the-sources-of-compositional-failure-in-vision-language-models-a-cont.html
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