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From Vision to Language: Investigating Causal Information Flow in Multimodal Decision-Making

Paper recorded by Signals 4 on 2026-09-04 in cs.CL. Abstract reproduced from arXiv; link to the original below.

Published 2026-09-04 on arXiv · recorded by Signals 4 on 2026-09-07

Category: cs.CL · 自然语言处理 · first seen 2026-09-07

Abstract

Vision-Language Models are commonly evaluated through their final predictions, but understanding whether these decisions are grounded in visual evidence requires tracing how visual information contributes to language-based decisions. With this purpose in mind, we investigate cross-modal information flow in a video-based generative multiple-choice-like setting by applying a layer-wise causal interv

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#107 most recent of 186 cs.CL papers we have recorded · ↑ newer: Large Language Models with At Most One Spike per Neuron · ↓ older: A Human-in-the-Loop Framework for AI-Assisted Scoring in Large-Scale W
Cite this page: From Vision to Language: Investigating Causal Information Flow in Multimodal Decision-Making: the #107 most recent of 186 cs.CL papers we have recorded (as of 2026-09-04). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/from-vision-to-language-investigating-causal-information-flow-in-multimodal-deci.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
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