FacTool: Factuality Detection in Generative AI

Detecting Deepfakes Without Seeing Any

This is official Pytorch code and datasets of the paper "Where Are the Facts? Searching for Fact-checked Information to Alleviate the Spread of Fake News", EMNLP 2020.

An easy to use framework for large-scale fact-checking and question answering

Adversarial Training on Transformer Networks to discover check-worthy factual claims

Codes for ACL-IJCNLP 2021 Paper "Zero-shot Fact Verification by Claim Generation"

Dataset and code for "Explainable Automated Fact-Checking for Public Health Claims" from EMNLP 2020.

Symmetric evaluation set based on the FEVER (fact verification) dataset

Resources for our AAAI 2022 paper: "LOREN: Logic-Regularized Reasoning for Interpretable Fact Verification".

This is the PyTorch code + data repository for paper "Hierarchical Multi-head Attentive Network for Evidence-aware Fake News Detection", EACL 2021

DeFactoNLP: An Automated Fact-checking System that uses Named Entity Recognition, TF-IDF vector comparison and Decomposable Attention models.

We construct and introduce DIALFACT, a testing benchmark dataset crowd-annotated conversational claims, paired with pieces of evidence from Wikipedia.

Code associated with the EMNLP 2024 Main paper: "Image, tell me your story!" Predicting the original meta-context of visual misinformation.

FEAT, short for Factcheck Explorer Analysis Tool, is designed to facilitate the exploration, analysis, and visualization of fact-checking data.

An Open-source Factuality Evaluation Demo for LLMs

Contains data, format checker, scorer and baselines for the CLEF2018 Fact Checking Lab.

Python wrapper for the Politifact REST API

Official implementation of the ACL 2023 paper: "Zero-shot Faithful Factual Error Correction"

This is the repository of code and dataset for paper "The Rise of Guardians: Fact-checking URL Recommendation to Combat Fake News", SIGIR 2018

Masking tokens to modify the predictions of a pretrained sentence classifier