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TalkSumm: A Dataset and Scalable Annotation Method for Scientific Paper Summarization Based on Conference Talks
- Guy Lev, Michal Shmueli-Scheuer, Jonathan Herzig, Achiya Jerbi, D. Konopnicki
- Computer ScienceACL
- 4 June 2019
This paper proposes a novel method that automatically generates summaries for scientific papers, by utilizing videos of talks at scientific conferences, and hypothesizes that such talks constitute a coherent and concise description of the papers’ content, and can form the basis for good summaries.
A Summarization System for Scientific Documents
A system that retrieves and summarizes scientific documents for a given information need, either in form of a free-text query or by choosing categorized values such as scientific tasks, datasets and more is presented.
Learning Object Detection from Captions via Textual Scene Attributes
- Achiya Jerbi, Roei Herzig, Jonathan Berant, Gal Chechik, A. Globerson
- Computer ScienceArXiv
- 30 September 2020
This work argues that captions contain much richer information about the image, including attributes of objects and their relations, and presents a method that uses the attributes in this "textual scene graph" to train object detectors.
orgFAQ: A New Dataset and Analysis on Organizational FAQs and User Questions
Frequently Asked Questions (FAQ) webpages are created by organizations for their users. FAQs are used in several scenarios, e.g., to answer user questions. On the other hand, the content of FAQs is…
J un 2 01 9 T ALK S UMM : A Dataset and Scalable Annotation Method for Scientific Paper Summarization Based on Conference Talks
Currently, no large-scale training data is available for the task of scientific paper summarization. In this paper, we propose a novel method that automatically generates summaries for scientific…