---
title: "Who cites A Richly Annotated Corpus for — 63 citing papers"
description: "63 papers of the Elamur Research library cite «A Richly Annotated Corpus for Different Tasks in Automated Fact-Checking», found in their…"
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---
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# Who cites «A Richly Annotated Corpus for Different Tasks in Automated Fact-Checking»

63 papers of our library cite it (of the 141,840 whose bibliographies we read) · 11 with a page here, the most cited first · [← back to «A Richly Annotated Corpus for Different Tasks in Automated Fact-Checking»](https://md.research.elamur.ai/free/en/papers/hanselowski-2019-richly-annotated-corpus-different-tasks/)

1. [**Fact or Fiction: Verifying Scientific Claims**David Wadden, Shanchuan Lin, Kyle Lo, et al.*2020 · 706 citations*](https://md.research.elamur.ai/free/en/papers/wadden-2020-fact-or-fiction-verifying-scientific/)
2. [**A Survey on Automated Fact-Checking**Zhijiang Guo, Michael Schlichtkrull, Andreas Vlachos*2022 · 646 citations*](https://md.research.elamur.ai/free/en/papers/guo-2022-survey-automated-fact-checking/)
3. [**Explainable Automated Fact-Checking for Public Health Claims**Neema Kotonya, Francesca Toni*2020 · 314 citations*](https://md.research.elamur.ai/free/en/papers/kotonya-2020-explainable-automated-fact-checking-public/)
4. [**A Survey on Stance Detection for Mis- and Disinformation Identification**Momchil Hardalov, Arnav Arora, Preslav Nakov, et al.*2022 · 187 citations*](https://md.research.elamur.ai/free/en/papers/hardalov-2022-survey-stance-detection-mis-disinformation/)
5. [**COVID-Fact: Fact Extraction and Verification of Real-World Claims on COVID-19 Pandemic**Arkadiy Saakyan, Tuhin Chakrabarty, Smaranda Muresan*2021 · 168 citations*](https://md.research.elamur.ai/free/en/papers/saakyan-2021-covid-fact-fact-extraction-verification/)
6. [**Evidence-based Fact-Checking of Health-related Claims**Mourad Sarrouti, Asma Ben Abacha, Yassine Mrabet, et al.*2021 · 129 citations*](https://md.research.elamur.ai/free/en/papers/sarrouti-2021-evidence-based-fact-checking-health/)
7. [**Cross-Domain Label-Adaptive Stance Detection**Momchil Hardalov, Arnav Arora, Preslav Nakov, et al.*2021 · 96 citations*](https://md.research.elamur.ai/free/en/papers/hardalov-2021-cross-domain-label-adaptive-stance/)
8. [**Complex Claim Verification with Evidence Retrieved in the Wild**Jifan Chen, Grace Kim, Aniruddh Sriram, et al.*2024 · 84 citations*](https://md.research.elamur.ai/free/en/papers/chen-2024-complex-claim-verification-evidence-retrieved/)
9. [**STANDER: An Expert-Annotated Dataset for News Stance Detection and Evidence Retrieval**Costanza Conforti, Jakob Berndt, Mohammad Taher Pilehvar, et al.*2020 · 22 citations*](https://md.research.elamur.ai/free/en/papers/conforti-2020-stander-expert-annotated-dataset-news/)
10. [**Topic-Guided Sampling For Data-Efficient Multi-Domain Stance Detection**Erik Arakelyan, Arnav Arora, Isabelle Augenstein*2023 · 19 citations*](https://md.research.elamur.ai/free/en/papers/arakelyan-2023-topic-guided-sampling-data-efficient/)
11. [**ARAFA: An LLM-Generated Arabic Fact-Checking Dataset**Christophe Khalil, Shady Elbassuoni, Rida Assaf*2026*](https://md.research.elamur.ai/free/en/papers/khalil-2026-arafa-llm-generated-arabic-fact/)

52 more papers of our library cite it; they have no page here yet.

- [← back to](https://md.research.elamur.ai/free/en/papers/hanselowski-2019-richly-annotated-corpus-different-tasks/) — A Richly Annotated Corpus for Different Tasks in Automated Fact-Checking