Does discourse structure help action prediction? A look at Correction Triangles.

Kate Thompson, Akshay Chaturvedi, Nicholas Asher


Abstract
An understanding of natural language corrections is essential for artificial agents that are meant to collaborate and converse with humans. We present some preliminary experiments using language-to-action models investigating whether discourse structure, in particular Correction relations, improves the action prediction capabilities of language-to-action models for simple block world tasks. We focus on scenarios in which a model must correct a previous action, and present a corpus of synthetic dialogues to help explain model performance.
Anthology ID:
2025.iwcs-main.16
Volume:
Proceedings of the 16th International Conference on Computational Semantics
Month:
September
Year:
2025
Address:
Düsseldorf, Germany
Editors:
Kilian Evang, Laura Kallmeyer, Sylvain Pogodalla
Venue:
IWCS
SIG:
SIGSEM
Publisher:
Association for Computational Linguistics
Note:
Pages:
166–174
Language:
URL:
https://aclanthology.org/2025.iwcs-main.16/
DOI:
Bibkey:
Cite (ACL):
Kate Thompson, Akshay Chaturvedi, and Nicholas Asher. 2025. Does discourse structure help action prediction? A look at Correction Triangles.. In Proceedings of the 16th International Conference on Computational Semantics, pages 166–174, Düsseldorf, Germany. Association for Computational Linguistics.
Cite (Informal):
Does discourse structure help action prediction? A look at Correction Triangles. (Thompson et al., IWCS 2025)
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PDF:
https://aclanthology.org/2025.iwcs-main.16.pdf