AIC CTU@FEVER 8: On-premise fact checking through long context RAG
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Abstract (arXiv)
In this paper, we present our fact-checking pipeline which has scored first in FEVER 8 shared task. Our fact-checking system is a simple two-step RAG pipeline based on our last year's submission. We show how the pipeline can be redeployed on-premise, achieving state-of-the-art fact-checking performance (in sense of Ev2R test-score), even under the constraint of a single NVidia A10 GPU, 23GB of graphical memory and 60s running time per claim.
Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). Builds on 7 of its 19 references that are in the map. First posted on arXiv 5 Aug 2025.
Builds on
7 of 19 references.
References · 7
- 2017Billion-scale similarity search with GPUscited by 2,497
- 2023AVeriTeC: A Dataset for Real-world Claim Verification with Evidence from the Webcited by 144
- 2024The Automated Verification of Textual Claims (AVeriTeC) Shared Taskcited by 29
- 2024Ev2R: Evaluating Evidence Retrieval in Automated Fact-Checkingcited by 18
- 2024HerO at AVeriTeC: The Herd of Open Large Language Models for Verifying Real-World Claimscited by 12
- 2024AIC CTU system at AVeriTeC: Re-framing automated fact-checking as a simple RAG taskcited by 8
- 2024Multi-hop Evidence Pursuit Meets the Web: Team Papelo at FEVER 2024cited by 3
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Citing papers per year: 2026: 3.
3 papers.
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