CiteSee: Augmenting Citations in Scientific Papers with Persistent and Personalized Historical Context-Reference-Cited by-同舟云学术

CiteSee: Augmenting Citations in Scientific Papers with Persistent and Personalized Historical Context

Published:2023-04-19 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems
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Author:

Chang Joseph Chee¹^ORCID,Zhang Amy X.²^ORCID,Bragg Jonathan¹^ORCID,Head Andrew³^ORCID,Lo Kyle¹^ORCID,Downey Doug¹^ORCID,Weld Daniel S.⁴^ORCID

Affiliation:

1. Allen Institute for AI, United States

2. University of Washington and Allen Institute for AI, United States

3. University of Pennsylvania, United States

4. Allen Institute for AI & University of Washington, United States

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3544548.3580847

Reference65 articles.

1. 2019. CHI ’19: Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems (Glasgow , Scotland Uk) . Association for Computing Machinery , New York, NY, USA . 2019. CHI ’19: Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems (Glasgow, Scotland Uk). Association for Computing Machinery, New York, NY, USA.

2. Elastic Documents: Coupling Text and Tables through Contextual Visualizations for Enhanced Document Reading

3. Scientific Paper Recommendation: A Survey

4. Physicists Reading Physics

5. Iz Beltagy Kyle Lo and Arman Cohan. 2019. SciBERT: A Pretrained Language Model for Scientific Text. In EMNLP. Iz Beltagy Kyle Lo and Arman Cohan. 2019. SciBERT: A Pretrained Language Model for Scientific Text. In EMNLP.

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