Overview of the TREC 2025 RAGTIME Track

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Authors: Dawn Lawrie, Sean MacAvaney, James Mayfield, Luca Soldaini, Eugene Yang, Andrew Yates
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Abstract

The principal goal of the RAG TREC Instrument for Multilingual Evaluation (RAGTIME) track at TREC is to study report generation from multilingual source documents. The track has created a document collection containing Arabic, Chinese, English, and Russian news stories. RAGTIME includes three task types: Multilingual Report Generation, English Report Generation, and Multilingual Information Retrieval (MLIR). A total of 125 runs were submitted by 13 participating teams (and as baselines by the track coordinators) for three tasks. This overview describes these three tasks and presents the available results.

Fields of Study & Subjects

Topic Modeling Information Retrieval and Search Behavior Natural Language Processing Techniques

Publication details

Journal / source
arXiv (Cornell University)
Publication date
10 February 2026
Language
EN
Document type
Preprint