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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
  • Institute for Advanced Computational Science
  • Stony Brook University
  • Guilan University

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

5 Scopus citations

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.

Original languageEnglish
Title of host publicationThe 62nd Annual Meeting of the Association for Computational Linguistics
Subtitle of host publicationFindings of the Association for Computational Linguistics, ACL 2024
EditorsLun-Wei Ku, Andre Martins, Vivek Srikumar
PublisherAssociation for Computational Linguistics (ACL)
Pages14815-14823
Number of pages9
ISBN (Electronic)9798891760998
DOIs
StatePublished - 2024
EventFindings of the 62nd Annual Meeting of the Association for Computational Linguistics, ACL 2024 - Hybrid, Bangkok, Thailand
Duration: Aug 11 2024Aug 16 2024

Publication series

NameProceedings of the Annual Meeting of the Association for Computational Linguistics
ISSN (Print)0736-587X

Conference

ConferenceFindings of the 62nd Annual Meeting of the Association for Computational Linguistics, ACL 2024
Country/TerritoryThailand
CityHybrid, Bangkok
Period08/11/2408/16/24

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