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Diagnosing the Reference Gap: What Visual Scaffolds Can and Cannot Fix in Multimodal Reasoning

Paper recorded by Signals 4 on 2026-10-29 in cs.CL. Abstract reproduced from arXiv; link to the original below.

Published 2026-10-29 on arXiv · recorded by Signals 4 on 2026-10-30

Category: cs.CL · 自然语言处理 · first seen 2026-10-30

Abstract

Multimodal large language models can recognize visual content yet struggle to reason reliably over it across multiple steps. In counting, a model may see all objects but lose track of which ones it has counted. We argue that such failures, commonly attributed to perception, reveal a reference gap: the failure to bind language to the relevant visual entities, regions, or locations. Motivated by the

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#85 most recent of 628 cs.CL papers we have recorded · ↑ newer: ARBITRA: Robust Document-Level ATT&CK Extraction via Multi-Expert Argu · ↓ older: GEPA-Curator: Curated Learning for Self Improving Agents
Cite this page: Diagnosing the Reference Gap: What Visual Scaffolds Can and Cannot Fix in Multimodal Reasoning: the #85 most recent of 628 cs.CL papers we have recorded (as of 2026-10-29). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/diagnosing-the-reference-gap-what-visual-scaffolds-can-and-cannot-fix-in-multimo.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
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