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        <title>Pragmatics in Language Grounding: Phenomena, Tasks, and Modeling Approaches</title>
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        <namePart type="given">Daniel</namePart>
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    <name type="personal">
        <namePart type="given">Aida</namePart>
        <namePart type="family">Nematzadeh</namePart>
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            <namePart type="given">Juan</namePart>
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        <name type="personal">
            <namePart type="given">Kalika</namePart>
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    <abstract>People rely heavily on context to enrich meaning beyond what is literally said, enabling concise but effective communication. To interact successfully and naturally with people, user-facing artificial intelligence systems will require similar skills in pragmatics: relying on various types of context — from shared linguistic goals and conventions, to the visual and embodied world — to use language effectively. We survey existing grounded settings and pragmatic modeling approaches and analyze how the task goals, environmental contexts, and communicative affordances in each work enrich linguistic meaning. We present recommendations for future grounded task design to naturally elicit pragmatic phenomena, and suggest directions that focus on a broader range of communicative contexts and affordances.</abstract>
    <identifier type="citekey">fried-etal-2023-pragmatics</identifier>
    <identifier type="doi">10.18653/v1/2023.findings-emnlp.840</identifier>
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        <date>2023-12</date>
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            <start>12619</start>
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%0 Conference Proceedings
%T Pragmatics in Language Grounding: Phenomena, Tasks, and Modeling Approaches
%A Fried, Daniel
%A Tomlin, Nicholas
%A Hu, Jennifer
%A Patel, Roma
%A Nematzadeh, Aida
%Y Bouamor, Houda
%Y Pino, Juan
%Y Bali, Kalika
%S Findings of the Association for Computational Linguistics: EMNLP 2023
%D 2023
%8 December
%I Association for Computational Linguistics
%C Singapore
%F fried-etal-2023-pragmatics
%X People rely heavily on context to enrich meaning beyond what is literally said, enabling concise but effective communication. To interact successfully and naturally with people, user-facing artificial intelligence systems will require similar skills in pragmatics: relying on various types of context — from shared linguistic goals and conventions, to the visual and embodied world — to use language effectively. We survey existing grounded settings and pragmatic modeling approaches and analyze how the task goals, environmental contexts, and communicative affordances in each work enrich linguistic meaning. We present recommendations for future grounded task design to naturally elicit pragmatic phenomena, and suggest directions that focus on a broader range of communicative contexts and affordances.
%R 10.18653/v1/2023.findings-emnlp.840
%U https://aclanthology.org/2023.findings-emnlp.840
%U https://doi.org/10.18653/v1/2023.findings-emnlp.840
%P 12619-12640

Markdown (Informal)

[Pragmatics in Language Grounding: Phenomena, Tasks, and Modeling Approaches](https://aclanthology.org/2023.findings-emnlp.840) (Fried et al., Findings 2023)

• Pragmatics in Language Grounding: Phenomena, Tasks, and Modeling Approaches (Fried et al., Findings 2023)

ACL

• Daniel Fried, Nicholas Tomlin, Jennifer Hu, Roma Patel, and Aida Nematzadeh. 2023. Pragmatics in Language Grounding: Phenomena, Tasks, and Modeling Approaches. In Findings of the Association for Computational Linguistics: EMNLP 2023, pages 12619–12640, Singapore. Association for Computational Linguistics.