Papers with role-oriented summaries

2 papers
CSDS: A Fine-Grained Chinese Dataset for Customer Service Dialogue Summarization (2021.emnlp-main)

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Challenge: Existing summarization methods are prone to generate redundant and incoherent summaries, causing the performance to be worse.
Approach: They propose a Chinese dataset for Customer Service Dialogue Summarization (CSDS) that provides role-oriented summaries to acquire different speakers' viewpoints.
Outcome: The proposed dataset improves the abstractive summaries in two aspects . it also provides role-oriented summary to acquire different speakers’ viewpoints .
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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