Views Are My Own, but Also Yours: Benchmarking Theory of Mind Using Common Ground

Fuente: arXiv
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Hauptverfasser: Soubki, Adil, Murzaku, John, Jordehi, Arash Yousefi, Zeng, Peter, Markowska, Magdalena, Mirroshandel, Seyed Abolghasem, Rambow, Owen
Format: Preprint
Veröffentlicht: 2024
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author Soubki, Adil
Murzaku, John
Jordehi, Arash Yousefi
Zeng, Peter
Markowska, Magdalena
Mirroshandel, Seyed Abolghasem
Rambow, Owen
author_facet Soubki, Adil
Murzaku, John
Jordehi, Arash Yousefi
Zeng, Peter
Markowska, Magdalena
Mirroshandel, Seyed Abolghasem
Rambow, Owen
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2403_02451
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Views Are My Own, but Also Yours: Benchmarking Theory of Mind Using Common Ground
Soubki, Adil
Murzaku, John
Jordehi, Arash Yousefi
Zeng, Peter
Markowska, Magdalena
Mirroshandel, Seyed Abolghasem
Rambow, Owen
Computation and Language
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.
title Views Are My Own, but Also Yours: Benchmarking Theory of Mind Using Common Ground
topic Computation and Language
url https://arxiv.org/abs/2403.02451