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The Alignment Illusion in Multimodal Large Language Models

Paper recorded by Signals 4 on 2026-09-24 in cs.LG. Abstract reproduced from arXiv; link to the original below.

Published 2026-09-24 on arXiv · recorded by Signals 4 on 2026-09-25

Category: cs.LG · 机器学习 · first seen 2026-09-25

Abstract

Layer-wise visual-text similarity in Multimodal Large Language Models (MLLMs) is widely interpreted as evidence that the language model progressively integrates visual content into a shared representation space. This reading rests on the assumption that scalar alignment scores reflect content-level cross-modal interaction. To test this assumption, we apply controlled interventions to the visual st

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#5 most recent of 293 cs.LG papers we have recorded · ↑ newer: Anchored Extra-Proximal Methods: Optimal Higher-Order Methods for Mono · ↓ older: Beyond Compression: Training Latent Representations for Stable Long-Ho
Cite this page: The Alignment Illusion in Multimodal Large Language Models: the #5 most recent of 293 cs.LG papers we have recorded (as of 2026-09-24). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/the-alignment-illusion-in-multimodal-large-language-models.html
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