ACL 2024findings4 citations
Views Are My Own, but Also Yours: Benchmarking Theory of Mind Using Common Ground
Adil Soubki, John Murzaku, Arash Yousefi Jordehi, Peter Zeng, Magdalena Markowska, Seyed Abolghasem Mirroshandel, Owen Rambow
Abstract
Evaluating the theory of mind (ToM) capabilities of language models (LMs) has recently received a great deal of attention. However, many existing benchmarks rely on synthetic data, which risks misaligning the resulting experiments with human behavior. We introduce the first ToM dataset based on naturally occurring spoken dialogs, Common-ToM, and show that LMs struggle to demonstrate ToM. We then show that integrating a simple, explicit representation of beliefs improves LM performance on Common-ToM.
BibTeX
@inproceedings{soubki-etal-2024-views,
title = "Views Are My Own, but Also Yours: Benchmarking Theory of Mind Using Common Ground",
author = "Soubki, Adil and
Murzaku, John and
Yousefi Jordehi, Arash and
Zeng, Peter and
Markowska, Magdalena and
Mirroshandel, Seyed Abolghasem and
Rambow, Owen",
editor = "Ku, Lun-Wei and
Martins, Andre and
Srikumar, Vivek",
booktitle = "Findings of the Association for Computational Linguistics: ACL 2024",
month = aug,
year = "2024",
address = "Bangkok, Thailand",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2024.findings-acl.880/",
doi = "10.18653/v1/2024.findings-acl.880",
pages = "14815--14823"
}