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Reliability-Aware Multimodal Sentiment Prediction Under Local Modality Missingness

Paper recorded by Signals 4 on 2026-10-14 in cs.CV. Abstract reproduced from arXiv; link to the original below.

Published 2026-10-14 on arXiv · recorded by Signals 4 on 2026-10-15

Category: cs.CV · 计算机视觉 · first seen 2026-10-15

Abstract

Multimodal sentiment models are usually evaluated on complete utterances, yet streams often lose a contiguous span of text, audio, or video. We study local missingness on aligned CMU-MOSEI features. Our reliability-aware network (RM-Net) keeps the original temporal positions, represents unobserved positions with a learned token, outputs bounded per-modality intensity contributions gated by observa

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#274 most recent of 756 cs.CV papers we have recorded · ↑ newer: Speculative Sampling in Interactive Video Generation · ↓ older: OLiVES: An Outdoor Low-Light Video Benchmark for Enhancement and Segme
Cite this page: Reliability-Aware Multimodal Sentiment Prediction Under Local Modality Missingness: the #274 most recent of 756 cs.CV papers we have recorded (as of 2026-10-14). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/reliability-aware-multimodal-sentiment-prediction-under-local-modality-missingne.html
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