Envisioning the Next-Gen Document Reader

• URL: http://arxiv.org/abs/2302.07492v1
• Date: Wed, 15 Feb 2023 06:43:12 GMT
• Title: Envisioning the Next-Gen Document Reader
• Authors: Catherine Yeh, Nedim Lipka, Franck Dernoncourt
• Abstract summary: We present our vision for the next-gen document reader that strives to enhance user understanding and create a more connected, trustworthy information experience. We describe 18 NLP-powered features to add to existing document readers and propose a novel plug-in marketplace that allows users to further customize their reading experience.
• Score: 41.35737889497044
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• Abstract: People read digital documents on a daily basis to share, exchange, and understand information in electronic settings. However, current document readers create a static, isolated reading experience, which does not support users' goals of gaining more knowledge and performing additional tasks through document interaction. In this work, we present our vision for the next-gen document reader that strives to enhance user understanding and create a more connected, trustworthy information experience. We describe 18 NLP-powered features to add to existing document readers and propose a novel plug-in marketplace that allows users to further customize their reading experience, as demonstrated through 3 exploratory UI prototypes available at https://github.com/catherinesyeh/nextgen-prototypes

Related papers

• RealitySummary: On-Demand Mixed Reality Document Enhancement using Large Language Models [13.906648004819107]
  We introduce RealitySummary, a mixed reality reading assistant that can enhance any printed or digital document using on-demand text extraction, summarization, and augmentation. We demonstrate real-time examples of six specific document augmentations: 1) summaries, 2) comparison tables, 3) timelines, 4) keyword lists, 5) summary highlighting, and 6) information cards.
  arXiv  Detail & Related papers  (2024-05-28T21:59:56Z)
• Knowledge-Driven Cross-Document Relation Extraction [3.868708275322908]
  Relation extraction (RE) is a well-known NLP application often treated as a sentence- or document-level task. We propose a novel approach, KXDocRE, that embed domain knowledge of entities with input text for cross-document RE.
  arXiv  Detail & Related papers  (2024-05-22T11:30:59Z)
• Non Linear Software Documentation with Interactive Code Examples [9.880887106904519]
  Casdoc documents are interactive resources centered around code examples for programmers. Explanations of the code elements are presented as annotations that the readers reveal based on their needs. We observed that interactive documents can contain more information than static documents without being distracting to readers.
  arXiv  Detail & Related papers  (2023-11-29T20:08:46Z)
• DocPedia: Unleashing the Power of Large Multimodal Model in the Frequency Domain for Versatile Document Understanding [91.17151775296234]
  This work presents DocPedia, a novel large multimodal model (LMM) for versatile OCR-free document understanding. Unlike existing work either struggle with high-resolution documents or give up the large language model thus vision or language ability constrained, our DocPedia directly processes visual input in the frequency domain rather than the pixel space.
  arXiv  Detail & Related papers  (2023-11-20T14:42:25Z)
• Understanding Documentation Use Through Log Analysis: An Exploratory Case Study of Four Cloud Services [14.104545948572836]
  We analyze documentation page-view logs from four cloud-based industrial services. By analyzing page-view logs for over 100,000 users, we find diverse patterns of documentation page visits. We propose documentation page-view log analysis as a feasible technique for design audits of documentation.
  arXiv  Detail & Related papers  (2023-10-16T20:37:29Z)
• Beyond the Chat: Executable and Verifiable Text-Editing with LLMs [87.84199761550634]
  Conversational interfaces powered by Large Language Models (LLMs) have recently become a popular way to obtain feedback during document editing. We present InkSync, an editing interface that suggests executable edits directly within the document being edited.
  arXiv  Detail & Related papers  (2023-09-27T00:56:17Z)
• The Semantic Reader Project: Augmenting Scholarly Documents through AI-Powered Interactive Reading Interfaces [54.2590226904332]
  We describe the Semantic Reader Project, a effort across multiple institutions to explore automatic creation of dynamic reading interfaces for research papers. Ten prototype interfaces have been developed and more than 300 participants and real-world users have shown improved reading experiences. We structure this paper around challenges scholars and the public face when reading research papers.
  arXiv  Detail & Related papers  (2023-03-25T02:47:09Z)
• Focused Attention Improves Document-Grounded Generation [111.42360617630669]
  Document grounded generation is the task of using the information provided in a document to improve text generation. This work focuses on two different document grounded generation tasks: Wikipedia Update Generation task and Dialogue response generation.
  arXiv  Detail & Related papers  (2021-04-26T16:56:29Z)
• Converse, Focus and Guess -- Towards Multi-Document Driven Dialogue [53.380996227212165]
  We propose a novel task, Multi-Document Driven Dialogue (MD3), in which an agent can guess the target document that the user is interested in by leading a dialogue. GuessMovie contains 16,881 documents, each describing a movie, and associated 13,434 dialogues. Our method significantly outperforms several strong baseline methods and is very close to human's performance.
  arXiv  Detail & Related papers  (2021-02-04T06:36:11Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.