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Showing 1 to 11 of 11 for “"document understanding"”.

  1. Consistent and efficient long document understanding

    Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2024-03-01 without embargo terms

    uiuc Repository record for Consistent and efficient long document understanding (opens in a new tab)

  2. Computational perception for multi-modal document understanding

    Multimodal documents occur in a variety of forms, as graphs in technical reports, diagrams in textbooks, and graphic designs in bulletins. Humans can efficiently process the visual and textual information contained within to make decisions on topics including business, healthcare, and science. …

    mit Repository record for Computational perception for multi-modal document understanding (opens in a new tab)

  3. M3D: Multimodal MultiDocument Fine-Grained Inconsistency Detection

    … is a highly challenging task that involves understanding how each factual assertion within the claim relates to a set of trusted source materials. Existing approaches often make coarse-grained predictions but fail to identify the specific aspects of the claim that are troublesome and the …

    vt Repository record for M3D: Multimodal MultiDocument Fine-Grained Inconsistency Detection (opens in a new tab)

  4. Arabic multi-document text summarisation

    Multi-document summarisation is the process of producing a single summary of a collection of related documents. Much of the current work on multi-document text summarisation is concerned with the English language; relevant resources are numerous and readily available. These resources include human …

    lancaster Repository record for Arabic multi-document text summarisation (opens in a new tab)

  5. Proposition-based summarization with a coherence-driven incremental model

    … which operate on meaning representations of documents have been neglected in the past, although they are a very promising and interesting class of methods for summarization and text understanding. In this thesis, I present one such summarizer, which uses the proposition as its meaning …

    cambridge Repository record for Proposition-based summarization with a coherence-driven incremental model (opens in a new tab)

  6. Scalable information extraction with large language models

    … question answering, and domain-specific document understanding. Although large language models (LLMs) have broadened the scope of IE through zero-shot and in-context extraction, scalable IE remains challenging in realistic settings, particularly for scientific and other specialized …

    temple Repository record for Scalable information extraction with large language models (opens in a new tab)

  7. Finding Relevant PDF Medical Journal Articles by the Content of Their Figures as well as Their Text

    … through large PDF medical journal article document collections for literature review purposes. Despite users' best efforts to form precise and accurate queries, it is often difficult to guess the right keywords to find all the related articles while finding a minimum number of unrelated …

    byu Repository record for Finding Relevant PDF Medical Journal Articles by the Content of Their Figures as well as Their Text (opens in a new tab)

  8. Instruction Mining from Images: Constructing a Synthetic Dataset for Multimodal Learning

    … που περιλαμβάνουν OCR-intensive reasoning, document understanding, chart reasoning και γενικό multimodal reasoning. Τα αποτελέσματα έδειξαν ότι η συνθετική multimodal supervision μπορεί να βελτιώσει αποτελεσματικά τις επιδόσεις των μοντέλων χωρίς σημαντική υποβάθμιση της γενίκευσης, ενώ …

    athens Repository record for Instruction Mining from Images: Constructing a Synthetic Dataset for Multimodal Learning (opens in a new tab)

  9. Mining entity and relation structures from text: An effort-light approach

    … mining tasks? While people can easily access the documents in a gigantic collection with the help of data management systems, they struggle to gain insights from such a large volume of text data: document understanding calls for in-depth content analysis, content analysis itself may require …

    uiuc Repository record for Mining entity and relation structures from text: An effort-light approach (opens in a new tab)