Overview - NeuCLIR 2024

Data | Results | Runs | Participants

Cross-language Information Retrieval (CLIR) has been studied at TREC and subsequent evaluation forums for more than twenty years, but recent advances in the application of deep learning to information retrieval (IR) warrant a new, large-scale effort that will enable exploration of classical and modern IR techniques for this task.

Track coordinator(s):

• Dawn Lawrie, Johns Hopkins University
• Sean MacAvaney, University of Glasgow
• James Mayfield, Johns Hopkins University
• Paul McNamee, Johns Hopkins University
• Douglas W. Oard, University of Maryland
• Luca Soldaini, Allen Institute for AI
• Eugene Yang, Johns Hopkins University

Tasks:

• fas: Farsi Retrieval
• rus: Russian Retrieval
• zho: Chinese Retrieval
• mlir: Multilingual Information Retrieval
• tech: Chinese Technical Document Retrieval
• report: Report Generation Pilot

Track Web Page: https://neuclir.github.io/

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