The second edition of the TREC Retrieval Augmented Generation (RAG) Track advances research on systems that integrate retrieval and generation to address complex, real-world information needs. Building on the foundation of the inaugural 2024 track, this year's challenge introduces long, multi-sentence narrative queries to better reflect the deep search task with the growing demand for reasoning-driven responses. Participants are tasked with designing pipelines that combine retrieval and generation while ensuring transparency and factual grounding. The track leverages the MS MARCO V2.1 corpus and employs a multi-layered evaluation framework encompassing relevance assessment, response completeness, attribution verification, and agreement analysis. By emphasizing multi-faceted narratives and attribution-rich answers from over 150 submissions this year, the TREC 2025 RAG Track aims to foster innovation in creating trustworthy, context-aware systems for retrieval augmented generation.

翻译：TREC 检索增强生成（RAG）赛道第二版旨在推动集成检索与生成以应对复杂现实世界信息需求的系统研究。在首届2024年赛道的基础上，今年的挑战引入了长篇、多句的叙述性查询，以更好地反映随着对推理驱动响应需求增长而出现的深度搜索任务。参赛者的任务是设计结合检索与生成的流程，同时确保透明度和事实依据。该赛道利用 MS MARCO V2.1 语料库，并采用一个多层评估框架，涵盖相关性评估、响应完整性、归因验证和一致性分析。通过强调来自今年超过150份提交作品的多方面叙述和富含归因的答案，TREC 2025 RAG 赛道旨在促进创建可信赖、上下文感知的检索增强生成系统的创新。