A Systematic Survey of Claim Verification: Corpora, Systems, and Case Studies (2025.findings-emnlp)
Copied to clipboard
| Challenge: | This survey analyses 198 studies published between January 2022 and March 2025 . |
| Approach: | This survey synthesizes recent advances in CV corpus creation and system design. |
| Outcome: | The results of this study are synthesized from 198 studies published between January 2022 and March 2025. |
Similar Papers
Claim Verification in the Age of Large Language Models: A Survey (2026.acl-srw)
Copied to clipboard
| Challenge: | Recent election cycles have seen a large number of false information spread across social media and news platforms. |
| Approach: | They propose a framework for automated claim verification using Large Language Models and Retrieval Augmented Generation. |
| Outcome: | The proposed frameworks are based on large-scale models and new methods such as Retrieval Augmented Generation (RAG). |
Automated Justification Production for Claim Veracity in Fact Checking: A Survey on Architectures and Approaches (2024.acl-long)
Copied to clipboard
| Challenge: | Current research focuses on predicting claim veracity through metadata analysis and language scrutiny, with an emphasis on justifying verdicts. |
| Approach: | They propose a comprehensive taxonomy for categorizing works based on various criteria and propose scalable methodologies for improving fact-checking explainability. |
| Outcome: | The proposed taxonomy identifies challenges while proposing future directions in fact-checking explainability. |
MultiFC: A Real-World Multi-Domain Dataset for Evidence-Based Fact Checking of Claims (D19-1)
Copied to clipboard
Isabelle Augenstein, Christina Lioma, Dongsheng Wang, Lucas Chaves Lima, Casper Hansen, Christian Hansen, Jakob Grue Simonsen
| Challenge: | Existing efforts to verify factual claims are limited by small datasets or artificially constructed datasets. |
| Approach: | They propose to use the largest publicly available dataset of naturally occurring factual claims for automatic claim verification. |
| Outcome: | The proposed model outperforms baseline models and evidence pages significantly. |
A Survey on Automated Fact-Checking (2022.tacl-1)
Copied to clipboard
| Challenge: | Fact-checking is an essential task in journalism due to the speed with which information and misinformation can spread in the media ecosystem. |
| Approach: | They propose to use natural language processing to automate fact-checking by identifying common concepts and defining definitions. |
| Outcome: | The proposed method can predict the veracity of claims using natural language processing, machine learning, and databases. |
Automated Fact Checking: Task Formulations, Methods and Future Directions (C18-1)
Copied to clipboard
| Challenge: | Recent research on fact checking has focused on misinformation . however, relevant papers and articles have been published in research communities that are unaware of each other and use inconsistent terminology. |
| Approach: | They propose avenues for future NLP research on automated fact checking . they highlight the use of evidence as an important distinguishing factor . |
| Outcome: | The proposed methods unify the task formulations and methodologies across papers and authors. |
Fact or Fiction: Verifying Scientific Claims (2020.emnlp-main)
Copied to clipboard
David Wadden, Shanchuan Lin, Kyle Lo, Lucy Lu Wang, Madeleine van Zuylen, Arman Cohan, Hannaneh Hajishirzi
| Challenge: | SciFact is a dataset of 1.4K expert-written scientific claims paired with evidence-containing abstracts annotated with labels and rationales. |
| Approach: | They construct a dataset of 1.4K scientific claims paired with evidence-containing abstracts annotated with labels and rationales to test their system. |
| Outcome: | The proposed system can verify claims related to COVID-19 by identifying evidence from the CORD-19 corpus. |
Towards Effective Extraction and Evaluation of Factual Claims (2025.acl-long)
Copied to clipboard
| Challenge: | Lack of a standardized evaluation framework impedes assessment and comparison of claim extraction methods. |
| Approach: | They propose a framework for evaluating claim extraction in the context of fact-checking . they also introduce Claimify, an LLM-based claim extraction method . |
| Outcome: | The proposed evaluation framework outperforms existing methods in the evaluation of claim extraction methods. |
Complex Claim Verification with Evidence Retrieved in the Wild (2024.naacl-long)
Copied to clipboard
| Challenge: | Prior work makes simplifying assumptions in retrieval that depart from real-world use cases: no access to evidence, access to curated evidence, or access to published evidence after a claim was made. |
| Approach: | They propose a pipeline to check claims using raw evidence from the web . they restrict their retriever to only search documents available prior to the claim's making . |
| Outcome: | The proposed method is based on a political claim dataset and shows that the evidence summary produced by the system is reliable and relevant to answering key questions. |
Explainable Automated Fact-Checking: A Survey (2020.coling-main)
Copied to clipboard
| Challenge: | Steady progress has been made in fact-checking and its orthogonal tasks. |
| Approach: | They propose to use fact-checking explanations to explain predictions by comparing existing explanations against desirable properties to find out what makes for good explanations. |
| Outcome: | The proposed explanations are compared against desirable properties and show how they may lead to improvements in the research area. |
WatClaimCheck: A new Dataset for Claim Entailment and Inference (2022.acl-long)
Copied to clipboard
| Challenge: | a dataset for automated fact checking is presented . premise articles are used to verify the veracity of claims . |
| Approach: | They propose a dataset for automated fact checking and an evaluation of state of the art algorithms. |
| Outcome: | The proposed model improves retrieval quality of passages in premise articles . the proposed model predicts claim veracity by inference from premise article . |