AIC CTU@FEVER 8: On-premise fact checking through long context RAG
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arXiv
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| Autori principali: | , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| _version_ | 1866916883951779840 |
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| author | Ullrich, Herbert Drchal, Jan |
| author_facet | Ullrich, Herbert Drchal, Jan |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2508_04390 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | AIC CTU@FEVER 8: On-premise fact checking through long context RAG Ullrich, Herbert Drchal, Jan Computation and Language Artificial Intelligence 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. |
| title | AIC CTU@FEVER 8: On-premise fact checking through long context RAG |
| topic | Computation and Language Artificial Intelligence |
| url | https://arxiv.org/abs/2508.04390 |