Papers with Multi-party dialogue discourse parsing

2 papers
Enhancing Multi-party Dialogue Discourse Parsing with Explanation Generation (2025.coling-main)

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Challenge: Multi-party dialogue discourse parsing is an important and challenging task in natural language processing.
Approach: They propose a model to integrate external knowledge from Large Language Models to analyze dialogue discourse structures and semantic relations between utterances in multi-party conversations.
Outcome: The proposed model outperforms the state-of-the-art (SOTA) models on two public datasets.
DraDDP: A Multimodal Multi-Party Dialogue Discourse Parsing Dataset (2026.findings-acl)

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Challenge: Existing studies on multi-party dialogue discourse parsing focus on textual modality and two-party dialog . et al., 2016) focused on text-based discourse parses, ignoring the complexity and richness of multimodal interactions in real-world scenarios.
Approach: They construct the first publicly available English multimodal dataset for multi-party dialogue discourse parsing based on American TV dramas.
Outcome: The proposed dataset contains 495 dialogue segments with 6,374 utterances and 9.1 hours of parallel video content, covering rich multi-party interaction scenarios.

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