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The Illusion of Balanced Multimodal Sentiment Analysis: Beyond the Limits of Optimization-Based Methods

arxiv.org/abs/2609.11247

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Updated 7 h ago · first seen 11 Sept 2026

paper_01M294G4M35DHS9GWGDM9MER20

Published
11 Sept 2026
T1 · 7 h ago
arXiv
2609.11247
T1 · 7 h ago
Category
cs.CL
T1 · 7 h ago

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9 claims · 9 properties

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https://arxiv.org/abs/2609.11247currentcurrentarXiv (Atom API + RSS)T1highdeterministic

Abstractabstract1

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Multimodal Sentiment Analysis (MSA) remains constrained by modality imbalance, yet the field continues to rely on optimization-based balancing methods that promise more than they deliver. We provide three contributions: 1) a unified evaluation framework testing gradient and loss-based balancing strategies under controlled settings; 2) a theoretical diagnosis explaining why these methods fail, as they conflate fitting speed with discriminative contribution; and 3) a research agenda toward held-out discriminative modality valuation. Experiments on CMU-MOSI and CMU-MOSEI reveal three shortcomings: no strategy reliably outperforms Late Concatenation; performance is sensitive to hyperparameters; and even ratio calibration fails to yield consistent gains. The core issue is fundamental: loss is not utility, and gradients are not importance. Modality imbalance remains unresolved, motivating utility estimation from held-out performance.currentcurrentarXiv (Atom API + RSS)T1highdeterministic

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newcurrentcurrentarXiv (Atom API + RSS)T1highdeterministic

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2609.11247currentcurrentarXiv (Atom API + RSS)T1highdeterministic

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Ioanna Kaffeza, Efthymios Georgiou, Alexandros PotamianoscurrentcurrentarXiv (Atom API + RSS)T1highdeterministic

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cs.CLcurrentcurrentarXiv (Atom API + RSS)T1highdeterministic

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https://arxiv.org/pdf/2609.11247currentcurrentarXiv (Atom API + RSS)T1highdeterministic

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cs.CLcurrentcurrentarXiv (Atom API + RSS)T1highdeterministic

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11 Sept 2026currentcurrentarXiv (Atom API + RSS)T1highdeterministic

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