Papers by Tianxiang Ma

1 papers
Emotion–Cause Pair Extraction in Conversations via Semantic Decoupling and Alignment (2026.findings-acl)

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Challenge: Emotion-Cause Pair Extraction in Conversations (ECPEC) aims to identify the set of causal relations between emotion utterances and their triggering causes within a dialogue.
Approach: They propose a framework for Emotion-Cause Pair Extraction in Conversations that decouples emotion-oriented semantics from cause-oriented ones and employs optimal transport to enable many-to-many and globally consistent emotion-cause matching.
Outcome: The proposed framework achieves state-of-the-art on several benchmark datasets.

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