{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,24]],"date-time":"2026-06-24T15:35:45Z","timestamp":1782315345789,"version":"3.54.5"},"reference-count":46,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2023,3,9]],"date-time":"2023-03-09T00:00:00Z","timestamp":1678320000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Artif. Intell."],"abstract":"<jats:p>Communication is a dynamic process through which interlocutors adapt to each other. In the development of conversational agents, this core aspect has been put aside for several years since the main challenge was to obtain conversational neural models able to produce utterances and dialogues that at least at the surface level are human-like. Now that this milestone has been achieved, the importance of paying attention to the dynamic and adaptive interactive aspects of language has been advocated in several position papers. In this paper, we focus on how a Speaker adapts to an interlocutor with different background knowledge. Our models undergo a pre-training phase, through which they acquire grounded knowledge by learning to describe an image, and an adaptive phase through which a Speaker and a Listener play a repeated reference game. Using a similar setting, previous studies focus on how conversational models create new conventions; we are interested, instead, in studying whether the Speaker learns from the Listener's mistakes to adapt to his background knowledge. We evaluate models based on Rational Speech Act (RSA), a likelihood loss, and a combination of the two. We show that RSA could indeed work as a backbone to drive the Speaker toward the Listener: in the combined model, apart from the improved Listener's accuracy, the language generated by the Speaker features the changes that signal adaptation to the Listener's background knowledge. Specifically, captions to unknown object categories contain more adjectives and less direct reference to the unknown objects.<\/jats:p>","DOI":"10.3389\/frai.2023.1017204","type":"journal-article","created":{"date-parts":[[2023,3,9]],"date-time":"2023-03-09T07:07:25Z","timestamp":1678345645000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["She adapts to her student: An expert pragmatic speaker tailoring her referring expressions to the Layman listener"],"prefix":"10.3389","volume":"6","author":[{"given":"Claudio","family":"Greco","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Diksha","family":"Bagade","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dieu-Thu","family":"Le","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Raffaella","family":"Bernardi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2023,3,9]]},"reference":[{"key":"B1","doi-asserted-by":"crossref","first-page":"1173","DOI":"10.18653\/v1\/D16-1125","article-title":"\u201cReasoning about pragmatics with neural listeners and speakers,\u201d","author":"Andreas","year":"2016","journal-title":"Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing"},{"key":"B2","doi-asserted-by":"crossref","first-page":"2829","DOI":"10.18653\/v1\/2022.acl-long.202","article-title":"\u201cLearning to mediate disparities towards pragmatic communication,\u201d","author":"Bao","year":"2022","journal-title":"Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)"},{"key":"B3","doi-asserted-by":"crossref","first-page":"1112","DOI":"10.18653\/v1\/2021.emnlp-main.85","article-title":"\u201cMindCraft: theory of mind modeling for situated dialogue in collaborative tasks,\u201d","author":"Bara","year":"2021","journal-title":"Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing"},{"key":"B4","first-page":"515","article-title":"\u201cGrounding as a collaborative process,\u201d","author":"Benotti","year":"2021","journal-title":"Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume"},{"key":"B5","author":"Bird","year":"2009","journal-title":"Natural Language Processing with Python: Analyzing Text with the Natural Language Toolkit"},{"key":"B6","doi-asserted-by":"crossref","DOI":"10.18653\/v1\/2020.emnlp-main.703","article-title":"\u201cExperience grounds language,\u201d","author":"Bisk","year":"2020","journal-title":"Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)"},{"key":"B7","doi-asserted-by":"crossref","first-page":"301","DOI":"10.1016\/S0079-7421(10)53008-1","article-title":"\u201cTwo minds, one dialog: coordinating speaking and understanding,\u201d","author":"Brennan","year":"2010","journal-title":"The Psychology of Learning and Motivation"},{"key":"B8","doi-asserted-by":"crossref","first-page":"1482","DOI":"10.1037\/0278-7393.22.6.1482","article-title":"Conceptual pacts and lexical choice in conversation","volume":"22","author":"Brennan","year":"1996","journal-title":"J. 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