Papers with encoded dialogue representation

1 papers
Improving Role-Oriented Dialogue Summarization with Interaction-Aware Contrastive Learning (2024.lrec-main)

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Challenge: Existing methods for encoding dialogues do not capture interaction information between roles, thus ignore interaction-related key information.
Approach: They propose a contrastive learning based interaction-aware model for the role-oriented dialogue summarization namely CIAM and use it to train the decoder to learn role-level interaction.
Outcome: The proposed model captures interaction information between different roles and produces informative summaries on two public datasets.

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