mlsanityData to 14 Oct 2026

Overview of the TREC 2024 NeuCLIR Track

arXiv 2509.14355 ↗First posted 17 Sep 2025cs.IRcited by 13

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Abstract (arXiv)

The principal goal of the TREC Neural Cross-Language Information Retrieval (NeuCLIR) track is to study the effect of neural approaches on cross-language information access. The track has created test collections containing Chinese, Persian, and Russian news stories and Chinese academic abstracts. NeuCLIR includes four task types: Cross-Language Information Retrieval (CLIR) from news, Multilingual Information Retrieval (MLIR) from news, Report Generation from news, and CLIR from technical documents. A total of 274 runs were submitted by five participating teams (and as baselines by the track coordinators) for eight tasks across these four task types. Task descriptions and the available results are presented.

Key facts. Cited by 13 papers in the map (data through 14 Oct 2026). First posted on arXiv 17 Sep 2025.

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Citing papers per year: 2025: 3; 2026: 10.

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