mlsanityData to 7 Oct 2026

Semantic Role Labeling Guided Multi-turn Dialogue ReWriter

arXiv 2010.01417 ↗First posted 3 Oct 2020cs.CL cs.AIcited by 15

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Abstract (arXiv)

For multi-turn dialogue rewriting, the capacity of effectively modeling the linguistic knowledge in dialog context and getting rid of the noises is essential to improve its performance. Existing attentive models attend to all words without prior focus, which results in inaccurate concentration on some dispensable words. In this paper, we propose to use semantic role labeling (SRL), which highlights the core semantic information of who did what to whom, to provide additional guidance for the rewriter model. Experiments show that this information significantly improves a RoBERTa-based model that already outperforms previous state-of-the-art systems.

Key facts. Cited by 15 papers in the map (data through 7 Oct 2026). First posted on arXiv 3 Oct 2020.

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Citing papers per year: 2021: 3; 2022: 6; 2023: 2; 2024: 1; 2025: 3.

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