Fact Checking
197 papers with code • 4 benchmarks • 8 datasets
Benchmarks
These leaderboards are used to track progress in Fact Checking
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Libraries
Use these libraries to find Fact Checking models and implementations
BEIR
VitaminC
Mocheg
Stanceosaurus
Spiced
STVD-FC
Most implemented papers
"Liar, Liar Pants on Fire": A New Benchmark Dataset for Fake News Detection
manideep2510/siamese-BERT-fake-news-detection-LIAR
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ACL 2017
In this paper, we present liar: a new, publicly available dataset for fake news detection.
A simple but tough-to-beat baseline for the Fake News Challenge stance detection task
Identifying public misinformation is a complicated and challenging task.
Unsupervised Dense Information Retrieval with Contrastive Learning
facebookresearch/contriever
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In this work, we explore the limits of contrastive learning as a way to train unsupervised dense retrievers and show that it leads to strong performance in various retrieval settings.
Explainable Tsetlin Machine framework for fake news detection with credibility score assessment
The proliferation of fake news, i. e., news intentionally spread for misinformation, poses a threat to individuals and society.
Fake News Detection on Social Media using Geometric Deep Learning
One of the main reasons is that often the interpretation of the news requires the knowledge of political or social context or 'common sense', which current NLP algorithms are still missing.
Evaluating the Factual Consistency of Abstractive Text Summarization
yuhui-zh15/FactCCX
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EMNLP 2020
Currently used metrics for assessing summarization algorithms do not account for whether summaries are factually consistent with source documents.
Fact Checking in Community Forums
Community Question Answering (cQA) forums are very popular nowadays, as they represent effective means for communities around particular topics to share information.
Automatic Fact-guided Sentence Modification
atulkum/pointer_summarizer
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This is a challenging constrained generation task, as the output must be consistent with the new information and fit into the rest of the existing document.
CheckThat! at CLEF 2020: Enabling the Automatic Identification and Verification of Claims in Social Media
Finally, the lab offers a fifth task that asks to predict the check-worthiness of the claims made in English political debates and speeches.
COVID-19 on Social Media: Analyzing Misinformation in Twitter Conversations
Komal7209/BackUp-Twitter-Sentiment-Analysis-
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The analysis is presented and updated on a publically accessible dashboard (https://usc-melady. github. io/COVID-19-Tweet-Analysis) to track the nature of online discourse and misinformation about COVID-19 on Twitter from March 1 - June 5, 2020.
