# AIC CTU@FEVER 8: On-premise fact checking through long context RAG

arXiv: https://arxiv.org/abs/2508.04390 · HTML: https://mlsanity.com/paper/2508.04390/

## 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 (most cited first, 7 of 7)

- [Billion-scale similarity search with GPUs](https://mlsanity.com/paper/1702.08734/) (2017)
- [AVeriTeC: A Dataset for Real-world Claim Verification with Evidence from the Web](https://mlsanity.com/paper/2305.13117/) (2023)
- [The Automated Verification of Textual Claims (AVeriTeC) Shared Task](https://mlsanity.com/paper/2410.23850/) (2024)
- [Ev2R: Evaluating Evidence Retrieval in Automated Fact-Checking](https://mlsanity.com/paper/2411.05375/) (2024)
- [HerO at AVeriTeC: The Herd of Open Large Language Models for Verifying Real-World Claims](https://mlsanity.com/paper/2410.12377/) (2024)
- [AIC CTU system at AVeriTeC: Re-framing automated fact-checking as a simple RAG task](https://mlsanity.com/paper/2410.11446/) (2024)
- [Multi-hop Evidence Pursuit Meets the Web: Team Papelo at FEVER 2024](https://mlsanity.com/paper/2411.05762/) (2024)

## Built on by (most cited first, 3 of 3)

- [VILLAIN at AVerImaTeC: Verifying Image-Text Claims via Multi-Agent Collaboration](https://mlsanity.com/paper/2602.04587/) (2026)
- [AIC CTU@AVerImaTeC: dual-retriever RAG for image-text fact checking](https://mlsanity.com/paper/2602.15190/) (2026)
- [Evaluating and Improving Evidence-Grounded Fact-Checking in LLMs via Multi-Round Evidence Ablation](https://mlsanity.com/paper/2609.08943/) (2026)

## 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.