mlsanityData to 14 Oct 2026

Determining the Credibility of Science Communication

arXiv 2105.14473 ↗First posted 30 May 2021cs.DL cs.CLcited by 4

Not on the map. Why?

Abstract (arXiv)

Most work on scholarly document processing assumes that the information processed is trustworthy and factually correct. However, this is not always the case. There are two core challenges, which should be addressed: 1) ensuring that scientific publications are credible -- e.g. that claims are not made without supporting evidence, and that all relevant supporting evidence is provided; and 2) that scientific findings are not misrepresented, distorted or outright misreported when communicated by journalists or the general public. I will present some first steps towards addressing these problems and outline remaining challenges.

Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). Builds on 17 of its 36 references that are in the map. First posted on arXiv 30 May 2021.

Builds on

17 of 36 references.

References · 17

  1. 2020Longformer: The Long-Document Transformercited by 3,413
  2. 2019SciBERT: A Pretrained Language Model for Scientific Textcited by 1,414
  3. 2018A Dataset of Peer Reviews (PeerRead): Collection, Insights and NLP Applicationscited by 136
  4. 2018Construction of the Literature Graph in Semantic Scholarcited by 118
  5. 2017SemEval 2017 Task 10: ScienceIE - Extracting Keyphrases and Relations from Scientific Publicationscited by 102
  6. 2019ScisummNet: A Large Annotated Corpus and Content-Impact Models for Scientific Paper Summarization with Citation Networkscited by 73
  7. 2020ReviewRobot: Explainable Paper Review Generation based on Knowledge Synthesiscited by 54
  8. 2017A Supervised Approach to Extractive Summarisation of Scientific Paperscited by 33
  9. 2020What Can We Do to Improve Peer Review in NLP?cited by 32
  10. 2020Transformer Based Multi-Source Domain Adaptationcited by 23
  11. 2020Examining Citations of Natural Language Processing Literaturecited by 20
  12. 2020Gender Gap in Natural Language Processing Research: Disparities in Authorship and Citationscited by 17
5 more
  1. 2021CiteWorth: Cite-Worthiness Detection for Improved Scientific Document Understandingcited by 17
  2. 2020Two Stage Transformer Model for COVID-19 Fake News Detection and Fact Checkingcited by 15
  3. 2017Multi-Task Learning of Keyphrase Boundary Classificationcited by 8
  4. 2020Longitudinal Citation Prediction using Temporal Graph Neural Networkscited by 8
  5. 2021University of Copenhagen Participation in TREC Health Misinformation Track 2020cited by 2

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2022: 2; 2023: 0; 2024: 1; 2025: 0; 2026: 1.

4 papers.