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        <title>InFillmore: Frame-Guided Language Generation with Bidirectional Context</title>
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    <name type="personal">
        <namePart type="given">Jiefu</namePart>
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        <namePart type="given">Nathaniel</namePart>
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    <name type="personal">
        <namePart type="given">Benjamin</namePart>
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            <namePart type="given">Lun-Wei</namePart>
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        <name type="personal">
            <namePart type="given">Ivan</namePart>
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    <abstract>We propose a structured extension to bidirectional-context conditional language generation, or “infilling,” inspired by Frame Semantic theory. Guidance is provided through one of two approaches: (1) model fine-tuning, conditioning directly on observed symbolic frames, and (2) a novel extension to disjunctive lexically constrained decoding that leverages frame semantic lexical units. Automatic and human evaluations confirm that frame-guided generation allows for explicit manipulation of intended infill semantics, with minimal loss in distinguishability from human-generated text. Our methods flexibly apply to a variety of use scenarios, and we provide an interactive web demo.</abstract>
    <identifier type="citekey">ou-etal-2021-infillmore</identifier>
    <identifier type="doi">10.18653/v1/2021.starsem-1.12</identifier>
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            <start>129</start>
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%0 Conference Proceedings
%T InFillmore: Frame-Guided Language Generation with Bidirectional Context
%A Ou, Jiefu
%A Weir, Nathaniel
%A Belyy, Anton
%A Yu, Felix
%A Van Durme, Benjamin
%Y Ku, Lun-Wei
%Y Nastase, Vivi
%Y Vulić, Ivan
%S Proceedings of *SEM 2021: The Tenth Joint Conference on Lexical and Computational Semantics
%D 2021
%8 August
%I Association for Computational Linguistics
%C Online
%F ou-etal-2021-infillmore
%X We propose a structured extension to bidirectional-context conditional language generation, or “infilling,” inspired by Frame Semantic theory. Guidance is provided through one of two approaches: (1) model fine-tuning, conditioning directly on observed symbolic frames, and (2) a novel extension to disjunctive lexically constrained decoding that leverages frame semantic lexical units. Automatic and human evaluations confirm that frame-guided generation allows for explicit manipulation of intended infill semantics, with minimal loss in distinguishability from human-generated text. Our methods flexibly apply to a variety of use scenarios, and we provide an interactive web demo.
%R 10.18653/v1/2021.starsem-1.12
%U https://aclanthology.org/2021.starsem-1.12
%U https://doi.org/10.18653/v1/2021.starsem-1.12
%P 129-142

Markdown (Informal)

[InFillmore: Frame-Guided Language Generation with Bidirectional Context](https://aclanthology.org/2021.starsem-1.12) (Ou et al., *SEM 2021)

• InFillmore: Frame-Guided Language Generation with Bidirectional Context (Ou et al., *SEM 2021)

ACL

• Jiefu Ou, Nathaniel Weir, Anton Belyy, Felix Yu, and Benjamin Van Durme. 2021. InFillmore: Frame-Guided Language Generation with Bidirectional Context. In Proceedings of *SEM 2021: The Tenth Joint Conference on Lexical and Computational Semantics, pages 129–142, Online. Association for Computational Linguistics.