mlsanityData to 7 Oct 2026

Exploring Text-transformers in AAAI 2021 Shared Task: COVID-19 Fake News Detection in English

arXiv 2101.02359 ↗First posted 7 Jan 2021cs.CL cs.AI cs.LGcited by 11

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Abstract (arXiv)

In this paper, we describe our system for the AAAI 2021 shared task of COVID-19 Fake News Detection in English, where we achieved the 3rd position with the weighted F1 score of 0.9859 on the test set. Specifically, we proposed an ensemble method of different pre-trained language models such as BERT, Roberta, Ernie, etc. with various training strategies including warm-up,learning rate schedule and k-fold cross-validation. We also conduct an extensive analysis of the samples that are not correctly classified. The code is available at:https://github.com/archersama/3rd-solution-COVID19-Fake-News-Detection-in-English.

Key facts. Cited by 11 papers in the map (data through 7 Oct 2026). Builds on 15 of its 20 references that are in the map. First posted on arXiv 7 Jan 2021.

Builds on

15 of 20 references.

References · 15

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3 more
  1. 2020Early Detection of Fake News by Utilizing the Credibility of News, Publishers, and Users Based on Weakly Supervised Learningcited by 23
  2. 2020Fake News Detection in Social Media using Graph Neural Networks and NLP Techniques: A COVID-19 Use-casecited by 12
  3. 2020Fake news agenda in the era of COVID-19: Identifying trends through fact-checking contentcited by 3

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 3; 2022: 3; 2023: 1; 2024: 2; 2025: 1; 2026: 1.

11 papers.