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LayoutLMv2: Multi-modal Pre-training for Visually-Rich Document Understanding., , , , , , , , , and 2 other author(s). CoRR, (2020)DiT: Self-supervised Pre-training for Document Image Transformer., , , , , and . ACM Multimedia, page 3530-3539. ACM, (2022)MarkupLM: Pre-training of Text and Markup Language for Visually Rich Document Understanding., , , and . ACL (1), page 6078-6087. Association for Computational Linguistics, (2022)Graph Convolutional Networks with Markov Random Field Reasoning for Social Spammer Detection., , , , and . AAAI, page 1054-1061. AAAI Press, (2020)LayoutLMv2: Multi-modal Pre-training for Visually-rich Document Understanding., , , , , , , , , and 2 other author(s). ACL/IJCNLP (1), page 2579-2591. Association for Computational Linguistics, (2021)Comparative Analysis of Multi-period Portfolio Strategies., , and . BIFE, page 266-269. IEEE Computer Society, (2009)XFUND: A Benchmark Dataset for Multilingual Visually Rich Form Understanding., , , , , , , and . ACL (Findings), page 3214-3224. Association for Computational Linguistics, (2022)DocBank: A Benchmark Dataset for Document Layout Analysis., , , , , , and . COLING, page 949-960. International Committee on Computational Linguistics, (2020)LayoutLM: Pre-training of Text and Layout for Document Image Understanding., , , , , and . KDD, page 1192-1200. ACM, (2020)OSWorld: Benchmarking Multimodal Agents for Open-Ended Tasks in Real Computer Environments., , , , , , , , , and 7 other author(s). CoRR, (2024)