Which one is banana man? Evaluating vision-language models in multi-turn pragmatic interpretation
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Computer Science > Computation and Language
arXiv:2608.29571 (cs)
[Submitted on 30 Aug 2026]
Title:Which one is banana man? Evaluating vision-language models in multi-turn pragmatic interpretation
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Abstract:Flexible adaptation to context and shared pragmatic intuitions contribute to smooth human conversation. Iterated reference games---in which players repeatedly pick out novel referents using language---present a test case for agents' ability to perform context-sensitive pragmatic reasoning in multi-turn linguistic environments. We tested humans and vision--language models on their ability to identify the intended meaning of descriptions produced in iterated reference games, varying the provided context in terms of amount, order, and relevance. While humans performed well consistently, the models we evaluated could make use of prior context to interpret humans' referring expressions, but they struggled to build up the relevant context to interpret those expressions effectively. Our results suggest that the models we evaluated lack core skills needed for efficient linguistic collaboration.
| Subjects: | Computation and Language (cs.CL) |
| Cite as: | arXiv:2608.29571 [cs.CL] |
| (or arXiv:2608.29571v1 [cs.CL] for this version) | |
| https://doi.org/10.48550/arXiv.2608.29571
arXiv-issued DOI via DataCite (pending registration)
|
Submission history
From: Alvin Wei Ming Tan [view email][v1] Sun, 30 Aug 2026 05:36:41 UTC (7,112 KB)
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View a PDF of the paper titled Which one is banana man? Evaluating vision-language models in multi-turn pragmatic interpretation, by Alvin Wei Ming Tan and 2 other authors
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