Papers › A Structure Self-Aware Model for Discourse Parsing on Multi-Party Dialogues
A Structure Self-Aware Model for Discourse Parsing on Multi-Party Dialogues
An-Hui Wang, Linfeng Song, Hui Jiang, Shaopeng Lai, Junfeng Yao, Min Zhang, Jinsong Su
Conversational discourse structures aim to describe how a dialogue is organised, thus they are helpful for dialogue understanding and response generation. This paper focuses on predicting discourse dependency structures for multi-party dialogues. Previous work adopts incremental methods that take the features from the already predicted discourse relations to help generate the next one. Although the inter-correlations among predictions are considered, we find that the error propagation is also very serious and hurts the overall performance. To alleviate error propagation, we propose a Structure Self-Aware (SSA) model, which adopts a novel edge-centric Graph Neural Network (GNN) to update the information between each Elementary Discourse Unit (EDU) pair layer by layer, so that expressive representations can be learned without historical predictions. In addition, we take auxiliary training signals (e.g. structure distillation) for better representation learning. Our model achieves the new state-of-the-art performances on two conversational discourse parsing benchmarks, largely outperforming the previous methods.
Code
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Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Discourse Parsing | Molweni | Struct-Aware | Link & Rel F1 | 58.4 | #5 of 7 | Archive leaderboard | report |
| Discourse Parsing | Molweni | Struct-Aware | Link F1 | 81.6 | #5 of 7 | Archive leaderboard | report |
| Discourse Parsing | STAC | Struct-Aware | Link & Rel F1 | 57.3 | #3 of 7 | Archive leaderboard | report |
| Discourse Parsing | STAC | Struct-Aware | Link F1 | 73.4 | #3 of 7 | Archive leaderboard | report |
Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.
Methods
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