Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-07-11T16:02:00.920066Z
Paper Citation Record · LEDGER
As of 11 August 2026, this Paper Citation Record lists 96 of 96 outbound references and 0 inbound Pith citation observations for arXiv:2607.04636.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-07-11T16:02:00.920066Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
96 of 96 outbound references displayed
External citation measurements
No source-named external measurement is stored.
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Enhancing Large Multimodal Models in Key Information Extraction via Scene-Aware Document Synthesis UNIKIE-BENCH: Benchmarking Large Multimodal Models for Key Information Extraction in Visual Documents
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Enhancing Large Multimodal Models in Key Information Extraction via Scene-Aware Document Synthesis Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers) , pages=
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Enhancing Large Multimodal Models in Key Information Extraction via Scene-Aware Document Synthesis ACM Computing Surveys , volume=
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Enhancing Large Multimodal Models in Key Information Extraction via Scene-Aware Document Synthesis Artificial Intelligence Review , volume=
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Enhancing Large Multimodal Models in Key Information Extraction via Scene-Aware Document Synthesis Spatial Dual-Modality Graph Reasoning for Key Information Extraction
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Enhancing Large Multimodal Models in Key Information Extraction via Scene-Aware Document Synthesis Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing , pages=
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Enhancing Large Multimodal Models in Key Information Extraction via Scene-Aware Document Synthesis 2019 International Conference on Document Analysis and Recognition , pages=
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Enhancing Large Multimodal Models in Key Information Extraction via Scene-Aware Document Synthesis Survey on Question Answering over Visually Rich Documents: Methods, Challenges, and Trends
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Enhancing Large Multimodal Models in Key Information Extraction via Scene-Aware Document Synthesis Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) , pages=
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Enhancing Large Multimodal Models in Key Information Extraction via Scene-Aware Document Synthesis Artificial Intelligence Review , year=
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Enhancing Large Multimodal Models in Key Information Extraction via Scene-Aware Document Synthesis 2020 25th International conference on pattern recognition (ICPR) , pages=
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Enhancing Large Multimodal Models in Key Information Extraction via Scene-Aware Document Synthesis Lang2Act: Fine-Grained Visual Reasoning through Self-Emergent Linguistic Toolchains
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Enhancing Large Multimodal Models in Key Information Extraction via Scene-Aware Document Synthesis Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing , pages=
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Enhancing Large Multimodal Models in Key Information Extraction via Scene-Aware Document Synthesis MDocAgent: A Multi-Modal Multi-Agent Framework for Document Understanding
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Enhancing Large Multimodal Models in Key Information Extraction via Scene-Aware Document Synthesis VRAG-RL: Empower Vision-Perception-Based RAG for Visually Rich Information Understanding via Iterative Reasoning with Reinforcement Learning
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Enhancing Large Multimodal Models in Key Information Extraction via Scene-Aware Document Synthesis Proceedings of the 30th ACM international conference on multimedia , pages=
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Enhancing Large Multimodal Models in Key Information Extraction via Scene-Aware Document Synthesis Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers) , pages=
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Enhancing Large Multimodal Models in Key Information Extraction via Scene-Aware Document Synthesis Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) , pages=
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Enhancing Large Multimodal Models in Key Information Extraction via Scene-Aware Document Synthesis Qwen2.5-VL Technical Report
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Enhancing Large Multimodal Models in Key Information Extraction via Scene-Aware Document Synthesis Proceedings of the 2024 conference on empirical methods in natural language processing , pages=
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Enhancing Large Multimodal Models in Key Information Extraction via Scene-Aware Document Synthesis Going Full-TILT Boogie on Document Understanding with Text-Image-Layout Transformer , booktitle =
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Enhancing Large Multimodal Models in Key Information Extraction via Scene-Aware Document Synthesis Advances in neural information processing systems , volume=
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Enhancing Large Multimodal Models in Key Information Extraction via Scene-Aware Document Synthesis Unresolved cited work
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Enhancing Large Multimodal Models in Key Information Extraction via Scene-Aware Document Synthesis Science China Information Sciences , volume=
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Enhancing Large Multimodal Models in Key Information Extraction via Scene-Aware Document Synthesis Proceedings of the AAAI conference on artificial intelligence , volume=
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Enhancing Large Multimodal Models in Key Information Extraction via Scene-Aware Document Synthesis Findings of the Association for Computational Linguistics: ACL 2024 , pages=
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Enhancing Large Multimodal Models in Key Information Extraction via Scene-Aware Document Synthesis What is the value of templates?
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Enhancing Large Multimodal Models in Key Information Extraction via Scene-Aware Document Synthesis Proceedings of the 31st International Conference on Computational Linguistics , pages=
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Enhancing Large Multimodal Models in Key Information Extraction via Scene-Aware Document Synthesis Focus Anywhere for Fine-grained Multi-page Document Understanding
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Enhancing Large Multimodal Models in Key Information Extraction via Scene-Aware Document Synthesis Proceedings of the AAAI Conference on Artificial Intelligence , volume=
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Enhancing Large Multimodal Models in Key Information Extraction via Scene-Aware Document Synthesis PDF-WuKong: A Large Multimodal Model for Efficient Long PDF Reading with End-to-End Sparse Sampling
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Enhancing Large Multimodal Models in Key Information Extraction via Scene-Aware Document Synthesis Document Parsing Unveiled: Techniques, Challenges, and Prospects for Structured Information Extraction
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Enhancing Large Multimodal Models in Key Information Extraction via Scene-Aware Document Synthesis ACM Transactions on Information Systems , volume=
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Enhancing Large Multimodal Models in Key Information Extraction via Scene-Aware Document Synthesis Findings of the Association for Computational Linguistics: EMNLP 2023 , pages=
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Enhancing Large Multimodal Models in Key Information Extraction via Scene-Aware Document Synthesis Neurocomputing , pages=
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Enhancing Large Multimodal Models in Key Information Extraction via Scene-Aware Document Synthesis Findings of the Association for Computational Linguistics: EMNLP 2023 , pages=
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Enhancing Large Multimodal Models in Key Information Extraction via Scene-Aware Document Synthesis arXiv preprint arXiv:2603.02789 , year=
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Enhancing Large Multimodal Models in Key Information Extraction via Scene-Aware Document Synthesis LayoutXLM: Multimodal Pre-training for Multilingual Visually-rich Document Understanding
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Enhancing Large Multimodal Models in Key Information Extraction via Scene-Aware Document Synthesis Proceedings of the IEEE/CVF conference on computer vision and pattern recognition , pages=
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Enhancing Large Multimodal Models in Key Information Extraction via Scene-Aware Document Synthesis Findings of the Association for Computational Linguistics: EMNLP 2022 , pages=
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Enhancing Large Multimodal Models in Key Information Extraction via Scene-Aware Document Synthesis Molmo2: Open Weights and Data for Vision-Language Models with Video Understanding and Grounding
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Enhancing Large Multimodal Models in Key Information Extraction via Scene-Aware Document Synthesis InternVL3.5: Advancing Open-Source Multimodal Models in Versatility, Reasoning, and Efficiency
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