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Corpus Conversion Service: A Machine Learning Platform to Ingest Documents at Scale.

, , , and . KDD, page 774-782. ACM, (2018)

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FETA: Towards Specializing Foundation Models for Expert Task Applications., , , , , , , , , and 3 other author(s). CoRR, (2022)Robust PDF Document Conversion using Recurrent Neural Networks., , , , , , , , , and . AAAI, page 15137-15145. AAAI Press, (2021)Corpus Conversion Service: A Machine Learning Platform to Ingest Documents at Scale., , , and . KDD, page 774-782. ACM, (2018)Matrix product state applications for the ALPS project., , , , , , , and . Comput. Phys. Commun., 185 (12): 3430-3440 (2014)DocLayNet: A Large Human-Annotated Dataset for Document-Layout Segmentation., , , , and . KDD, page 3743-3751. ACM, (2022)Corpus Conversion Service: A machine learning platform to ingest documents at scale Poster abstract., , , and . CoRR, (2018)FETA: Towards Specializing Foundational Models for Expert Task Applications., , , , , , , , , and 3 other author(s). NeurIPS, (2022)ICDAR 2023 Competition on Robust Layout Segmentation in Corporate Documents., , , , , and . ICDAR (2), volume 14188 of Lecture Notes in Computer Science, page 471-482. Springer, (2023)INDUS: Effective and Efficient Language Models for Scientific Applications., , , , , , , , , and 24 other author(s). CoRR, (2024)ESG Accountability Made Easy: DocQA at Your Service., , , , , , , , , and 4 other author(s). CoRR, (2023)