LongDocURL
PulseAugur coverage of LongDocURL — every cluster mentioning LongDocURL across labs, papers, and developer communities, ranked by signal.
1 day(s) with sentiment data
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D2-ScaleAgent framework enhances long document understanding
Researchers have introduced D2-ScaleAgent, a novel framework designed to enhance the understanding of long and visually rich documents. This agentic system employs a dual-dimensional scaling paradigm, dynamically adjust…
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New benchmarks and frameworks tackle extra-long document understanding
Researchers have introduced two new frameworks for improving the ability of large language models to understand and answer questions from very long documents. DocTrace focuses on creating a traceable evidence graph to s…
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HierDoc framework enhances long-document visual question answering
Researchers have developed HierDoc, a novel framework for long-document visual question answering that improves evidence retrieval by employing a hierarchical approach. This method first selects relevant pages from a do…
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New VLD-RAG framework enhances AI's ability to process long, visual documents
Researchers have developed VLD-RAG, a novel agentic framework designed for retrieval-augmented generation over long, visually-rich documents. This system constructs a multimodal index that preserves page layout and inco…
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MAGE-RAG framework enhances multimodal QA for long documents
Researchers have introduced MAGE-RAG, a novel framework designed to improve multimodal question answering for long documents. This system constructs an adaptive graph of evidence, incorporating text, images, tables, and…
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EviProp method improves long document retrieval with graph diffusion
Researchers have developed EviProp, a novel method for retrieving relevant pages from long, visually rich documents. Unlike existing approaches that score pages independently, EviProp models documents as multimodal Chun…