Learning Robust Pair Confidence for Multimodal Emotion-Cause Pair Extraction

arXiv:2606.18893v1 Announce Type: new Abstract: Multimodal emotion-cause pair extraction (MECPE) requires reliable pair confidence over candidate pairs. Existing pair scorers commonly use pair-level cross entropy over valid candidates, which treats links mostly independently. This leaves the relative confidence geometry among competing causes under-constrained, allowing gold pairs to stay close to hard negatives or rely on incidental non-gold context. We study this vulnerability as pair-confidence brittleness and propose RPCL (Robust Pair Confidence Learning), a training-only framework for pai

Source: arXiv cs.CL — read the full report at the original publisher.

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