mlsanityData to 7 Oct 2026

Overview of the TREC 2025 RAGTIME Track

arXiv 2602.10024 ↗First posted 10 Feb 2026cs.IR cs.CLcited by 5

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Abstract (arXiv)

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.

Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). Builds on 3 of its 6 references that are in the map. First posted on arXiv 10 Feb 2026.

Builds on

3 of 6 references.

References · 3

  1. 2024On the Evaluation of Machine-Generated Reportscited by 23
  2. 2024Translate-Distill: Learning Cross-Language Dense Retrieval by Translation and Distillationcited by 22
  3. 2025Auto-ARGUE: LLM-Based Report Generation Evaluationcited by 14

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2026: 5.

5 papers.

  1. 2026CoverageBench: Evaluating Information Coverage across Tasks and Domainscited by 2
  2. 2026DoGMaTiQ: Automated Generation of Question-and-Answer Nuggets for Report Evaluationcited by 1
  3. 2026LLM Olympiad: Why Model Evaluation Needs a Sealed Examcited by 0
  4. 2026Assessing the Downstream Utility of Evidence-Aware Retrieval in RAGcited by 0
  5. 2026Knowledge Pull Requests for Continual Document Authoringcited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2026Overview of the TREC 2025 Retrieval Augmented Generation (RAG) Track
  2. 2024Ragnar"ok: A Reusable RAG Framework and Baselines for TREC 2024 Retrieval-Augmented Generation Track
  3. 2024Initial Nugget Evaluation Results for the TREC 2024 RAG Track with the AutoNuggetizer Framework
  4. 2025Support Evaluation for the TREC 2024 RAG Track: Comparing Human versus LLM Judges
  5. 2025Multilingual Retrieval-Augmented Generation for Knowledge-Intensive Task
  6. 2024Enhancing Multilingual Information Retrieval in Mixed Human Resources Environments: A RAG Model Implementation for Multicultural Enterprise
  7. 2025The Cross-Lingual Cost: Retrieval Biases in RAG over Arabic-English Corpora
  8. 2026Resources for Automated Evaluation of Assistive RAG Systems that Help Readers with News Trustworthiness Assessment