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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. T07-11Similar problemSince 2025

    JSONSchemaBench: A Rigorous Benchmark of Structured Outputs for Language Models

    Authors
    Saibo Geng, Hudson Cooper, Michał Moskal, Samuel Jenkins, Julian Berman, Nathan Ranchin, Robert West, Eric Horvitz, Harsha Nori
    Year
    2025
    Venue
    arXiv

    Korean review of T07-11

  3. 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

  4. 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

  5. T07-3Similar problem

    TableFormer: Table Structure Understanding with Transformers

    Authors
    Ahmed Nassar, Nikolaos Livathinos, Maksym Lysak, Peter Staar
    Year
    2022
    Venue
    CVPR 2022

    Korean review of T07-3

  6. T07-4Candidate approach

    Nougat: Neural Optical Understanding for Academic Documents

    Authors
    Lukas Blecher, Guillem Cucurull, Thomas Scialom, Robert Stojnic
    Year
    2023
    Venue
    arXiv (Meta AI)

    Korean review of T07-4

  7. T07-5Similar problem

    FUNSD: A Dataset for Form Understanding in Noisy Scanned Documents

    Authors
    Guillaume Jaume, Hazim Kemal Ekenel, Jean-Philippe Thiran
    Year
    2019
    Venue
    ICDAR 2019 OST (Workshop on Open Services and Tools for Document Analysis)

    Korean review of T07-5

  8. T07-6Similar problem

    DocVQA: A Dataset for VQA on Document Images

    Authors
    Minesh Mathew, Dimosthenis Karatzas, C.V. Jawahar
    Year
    2021
    Venue
    WACV 2021

    Korean review of T07-6

  9. 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

  10. 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

  11. 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

  12. T07-12Similar problem

    Let Me Speak Freely? A Study On The Impact Of Format Restrictions On Large Language Model Performance

    Authors
    Zhi Rui Tam, Cheng-Kuang Wu, Yi-Lin Tsai, Chieh-Yen Lin, Hung-yi Lee, Yun-Nung Chen
    Year
    2024
    Venue
    EMNLP 2024 Industry Track

    Korean review of T07-12

  13. T07-13Similar problem

    Grammar-Aligned Decoding

    Authors
    Kanghee Park, Jiayu Wang, Taylor Berg-Kirkpatrick, Nadia Polikarpova, Loris D'Antoni
    Year
    2024
    Venue
    NeurIPS 2024

    Korean review of T07-13

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