RAVE: Retrieval and Scoring Aware Verifiable Claim Detection
Not on the map. Why?
Abstract (arXiv)
The rapid spread of misinformation on social media underscores the need for scalable fact-checking tools. A key step is claim detection, which identifies statements that can be objectively verified. Prior approaches often rely on linguistic cues or claim check-worthiness, but these struggle with vague political discourse and diverse formats such as tweets. We present RAVE (Retrieval and Scoring Aware Verifiable Claim Detection), a framework that combines evidence retrieval with structured signals of relevance and source credibility. Experiments on CT22-test and PoliClaim-test show that RAVE consistently outperforms text-only and retrieval-based baselines in both accuracy and F1.
Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 8 of its 19 references that are in the map. First posted on arXiv 19 Sep 2025.
Builds on
8 of 19 references.
References · 8
- 2017Detection and Resolution of Rumours in Social Media: A Surveycited by 104
- 2018Towards Automated Factchecking: Developing an Annotation Schema and Benchmark for Consistent Automated Claim Detectioncited by 55
- 2024Claim Detection for Automated Fact-checking: A Survey on Monolingual, Multilingual and Cross-Lingual Researchcited by 35
- 2024AFaCTA: Assisting the Annotation of Factual Claim Detection with Reliable LLM Annotatorscited by 28
- 2018ClaimRank: Detecting Check-Worthy Claims in Arabic and Englishcited by 27
- 2020Accenture at CheckThat! 2020: If you say so: Post-hoc fact-checking of claims using transformer-based modelscited by 15
- 2024FactFinders at CheckThat! 2024: Refining Check-worthy Statement Detection with LLMs through Data Pruningcited by 6
- 2020Information Credibility in the Social Web: Contexts, Approaches, and Open Issuescited by 1
Built on by
Citing papers per year: 2026: 1.
1 paper.