Learning to fuse sentences with transformers for summarization

    公开(公告)号:US11620457B2

    公开(公告)日:2023-04-04

    申请号:US17177372

    申请日:2021-02-17

    Applicant: ADOBE INC.

    Abstract: Systems and methods for sentence fusion are described. Embodiments receive coreference information for a first sentence and a second sentence, wherein the coreference information identifies entities associated with both a term of the first sentence and a term of the second sentence, apply an entity constraint to an attention head of a sentence fusion network, wherein the entity constraint limits attention weights of the attention head to terms that correspond to a same entity of the coreference information, and predict a fused sentence using the sentence fusion network based on the entity constraint, wherein the fused sentence combines information from the first sentence and the second sentence.

    LEARNING TO FUSE SENTENCES WITH TRANSFORMERS FOR SUMMARIZATION

    公开(公告)号:US20220261555A1

    公开(公告)日:2022-08-18

    申请号:US17177372

    申请日:2021-02-17

    Applicant: ADOBE INC.

    Abstract: Systems and methods for sentence fusion are described. Embodiments receive coreference information for a first sentence and a second sentence, wherein the coreference information identifies entities associated with both a term of the first sentence and a term of the second sentence, apply an entity constraint to an attention head of a sentence fusion network, wherein the entity constraint limits attention weights of the attention head to terms that correspond to a same entity of the coreference information, and predict a fused sentence using the sentence fusion network based on the entity constraint, wherein the fused sentence combines information from the first sentence and the second sentence.

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