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Lost in Perception: Isolating Perceptual and Reasoning Failures in Multimodal Physics and Geometry Reasoning

Published 17 Sept 2026arXiv:2609.18991

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Updated 24 h ago · first seen 17 Sept 2026

paper_01M2Q5D3VA2XZ3YPSX73W4HVS5

Abstract

Multimodal LLMs report strong performance on scientific reasoning benchmarks, yet most treat perception and reasoning as a single measurable process. We introduce a five-task diagnostic experiment across physics and geometry benchmarks that isolates failures to perception, reasoning, or both. Incorrect diagram interpretation degrades performance even on problems models solve correctly from text alone, and accuracy generally rises from raw images to human-authored captions. Recovery under corrected captions is high for some models, separating perception-blocked failures from genuine reasoning bottlenecks. Which reasoning error follows a perception failure depends on domain: physics failures resolve into calculation errors, geometry into conceptual misapplication. As a discussion beyond our core experiments, InternS1-mini, despite heavy scientific pretraining and thinking capabilities, falls below the weakest model from experiments on every task, with reasoning traces frequently truncating before completion.

Authors

Authors 6

Dhruvkumar PatelRaj JaiswalRajiv Ratn ShahRia KhatoniarSree Krishna UppalapatiTanuja Ganu

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arXiv (Atom API + RSS)rss.arxiv.org/rss/cs.AI feedT1· Official9 h ago7

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