End-to-End Neural Discourse Deixis Resolution in Dialogue

November 29, 2022 ยท Declared Dead ยท ๐Ÿ› Conference on Empirical Methods in Natural Language Processing

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Authors Shengjie Li, Vincent Ng arXiv ID 2211.15980 Category cs.CL: Computation & Language Citations 1 Venue Conference on Empirical Methods in Natural Language Processing Last Checked 5 months ago
Abstract
We adapt Lee et al.'s (2018) span-based entity coreference model to the task of end-to-end discourse deixis resolution in dialogue, specifically by proposing extensions to their model that exploit task-specific characteristics. The resulting model, dd-utt, achieves state-of-the-art results on the four datasets in the CODI-CRAC 2021 shared task.
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