DEAR: Distributional Error-Aware Reliability for Robust Multimodal Sentiment Analysis with Missing Modalities (2026.findings-acl)
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| Challenge: | Existing methods focus on feature completion but neglect semantic shifts caused by distribution gaps and decision risks under high uncertainty. |
| Approach: | They propose a distributional error-aware reliability estimation framework for robust MSA . they propose reconstructed features to be explicitly aligned with original distributional manifold . |
| Outcome: | The proposed framework mitigates semantic shifts by aligning reconstructed features with original distributional manifold . Extensive experiments on MOSI, MOSEI, and SIMS validate the framework . |
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