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
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.
KILT: a Benchmark for Knowledge Intensive Language Tasks
We test both task-specific and general baselines, evaluating downstream performance in addition to the ability of the models to provide provenance.
Team Alex at CLEF CheckThat! 2020: Identifying Check-Worthy Tweets With Transformer Models
LiamMaclean216/Pytorch-Transfomer
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While misinformation and disinformation have been thriving in social media for years, with the emergence of the COVID-19 pandemic, the political and the health misinformation merged, thus elevating the problem to a whole new level and giving rise to the first global infodemic.
Evidence-based Factual Error Correction
j6mes/2021-acl-factual-error-correction
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This paper introduces the task of factual error correction: performing edits to a claim so that the generated rewrite is better supported by evidence.
Editing Factual Knowledge in Language Models
nicola-decao/KnowledgeEditor
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EMNLP 2021
We present KnowledgeEditor, a method which can be used to edit this knowledge and, thus, fix 'bugs' or unexpected predictions without the need for expensive re-training or fine-tuning.
MultiVerS: Improving scientific claim verification with weak supervision and full-document context
dwadden/longchecker
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Findings (NAACL) 2022
Our approach outperforms two competitive baselines on three scientific claim verification datasets, with particularly strong performance in zero / few-shot domain adaptation experiments.
SelfCheckGPT: Zero-Resource Black-Box Hallucination Detection for Generative Large Language Models
In this work, we propose "SelfCheckGPT", a simple sampling-based approach that can be used to fact-check the responses of black-box models in a zero-resource fashion, i. e. without an external database.
ProjE: Embedding Projection for Knowledge Graph Completion
Sujit-O/pykg2vec
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In this work, we present a shared variable neural network model called ProjE that fills-in missing information in a knowledge graph by learning joint embeddings of the knowledge graph's entities and edges, and through subtle, but important, changes to the standard loss function.
``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.
TI-CNN: Convolutional Neural Networks for Fake News Detection
By projecting the explicit and latent features into a unified feature space, TI-CNN is trained with both the text and image information simultaneously.
