AIC CTU@FEVER 8：通过长上下文RAG进行本地事实核查
AIC CTU@FEVER 8: On-premise fact checking through long context RAG
AI总结：
本文提出一个基于长上下文RAG的两步事实核查流水线，在FEVER 8任务中排名第一，并能在单GPU本地部署下达到最先进性能。
摘要：
在本文中，我们介绍了在FEVER 8共享任务中排名第一的事实核查流水线。我们的事实核查系统是一个基于去年提交的简单两步RAG流水线。我们展示了该流水线如何重新部署到本地，在单个NVIDIA A10 GPU、23GB显存和每条声明60秒运行时间的约束下，实现了最先进的事实核查性能（就Ev2R测试分数而言）。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
