Fact-Checking

Are Large Language Models Reliable Judges? A Study on the Factuality Evaluation Capabilities of LLMs EMNLP 2023 Automated Fact-Checking in Dialogue: Are Specialized Models Needed? EMNLP 2023 Automatic Evaluation of Attribution by Large Language Models EMNLP 2023 AVeriTeC: A Dataset for Real-world Claim Verification with Evidence from the Web NeurIPS 2023 BEVERS: A General, Simple, and Performant Framework for Automatic Fact Verification EACL 2023 bgGLUE: A Bulgarian General Language Understanding Evaluation Benchmark ACL 2023 BoardgameQA: A Dataset for Natural Language Reasoning with Contradictory Information NeurIPS 2023 CARE-MI: Chinese Benchmark for Misinformation Evaluation in Maternity and Infant Care NeurIPS 2023 Check-COVID: Fact-Checking COVID-19 News Claims with Scientific Evidence ACL 2023 ClaimDiff: Comparing and Contrasting Claims on Contentious Issues ACL 2023 Claim-Dissector: An Interpretable Fact-Checking System with Joint Re-ranking and Veracity Prediction ACL 2023 Converge to the Truth: Factual Error Correction via Iterative Constrained Editing AAAI 2023 CoP: Factual Inconsistency Detection by Controlling the Preference AAAI 2023 COVID-VTS: Fact Extraction and Verification on Short Video Platforms EACL 2023 CREPE: Open-Domain Question Answering with False Presuppositions ACL 2023 Decker: Double Check with Heterogeneous Knowledge for Commonsense Fact Verification ACL 2023 Detecting and Mitigating Hallucinations in Multilingual Summarisation EMNLP 2023 Detecting Contradictory COVID-19 Drug Efficacy Claims from Biomedical Literature ACL 2023 Enhancing Information Retrieval in Fact Extraction and Verification EACL 2023 Enhancing Structured Evidence Extraction for Fact Verification EMNLP 2023 Enhancing Uncertainty-Based Hallucination Detection with Stronger Focus EMNLP 2023 Entity-Aware Dual Co-Attention Network for Fake News Detection EACL 2023 Evaluating the Factual Consistency of Large Language Models Through News Summarization ACL 2023 Explainable Claim Verification via Knowledge-Grounded Reasoning with Large Language Models EMNLP 2023 EXPLAIN, EDIT, GENERATE: Rationale-Sensitive Counterfactual Data Augmentation for Multi-hop Fact Verification EMNLP 2023