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T07. Structured output, schema validation, and document understanding

Research on forcing machine-checkable output and reading business documents.

  1. T07-10Structural parallelSince 2025

    XGrammar: Flexible and Efficient Structured Generation Engine for Large Language Models

    Authors
    Yixin Dong, Charlie F. Ruan, Yaxing Cai, Ruihang Lai, Ziyi Xu, Yilong Zhao, Tianqi Chen
    Year
    2025
    Venue
    MLSys 2025

    Korean review of T07-10

  2. T07-1Structural parallel

    LayoutLMv3: Pre-training for Document AI with Unified Text and Image Masking

    Authors
    Yupan Huang, Tengchao Lv, Lei Cui, Yutong Lu, Furu Wei
    Year
    2022
    Venue
    ACM Multimedia 2022 (ACM MM)

    Korean review of T07-1

  3. T07-2Structural parallel

    OCR-free Document Understanding Transformer

    Authors
    Geewook Kim, Teakgyu Hong, Moonbin Yim, Jeongyeon Nam, Jinyoung Park, Jinyeong Yim, Wonseok Hwang, Sangdoo Yun, Dongyoon Han, Seunghyun Park
    Year
    2022
    Venue
    ECCV 2022

    Korean review of T07-2

  4. T07-7Structural parallel

    PICARD: Parsing Incrementally for Constrained Auto-Regressive Decoding from Language Models

    Authors
    Torsten Scholak, Nathan Schucher, Dzmitry Bahdanau
    Year
    2021
    Venue
    EMNLP 2021

    Korean review of T07-7

  5. T07-8Structural parallel

    Grammar-Constrained Decoding for Structured NLP Tasks without Finetuning

    Authors
    Saibo Geng, Martin Josifoski, Maxime Peyrard, Robert West
    Year
    2023
    Venue
    EMNLP 2023

    Korean review of T07-8

  6. T07-9Structural parallel

    Efficient Guided Generation for Large Language Models

    Authors
    Brandon T. Willard, Rémi Louf
    Year
    2023
    Venue
    arXiv, Outlines

    Korean review of T07-9

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