Patapasco: A Python Framework for Cross-Language Information Retrieval Experiments
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Abstract (arXiv)
While there are high-quality software frameworks for information retrieval experimentation, they do not explicitly support cross-language information retrieval (CLIR). To fill this gap, we have created Patapsco, a Python CLIR framework. This framework specifically addresses the complexity that comes with running experiments in multiple languages. Patapsco is designed to be extensible to many language pairs, to be scalable to large document collections, and to support reproducible experiments driven by a configuration file. We include Patapsco results on standard CLIR collections using multiple settings.
Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). First posted on arXiv 24 Jan 2022.
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Citing papers per year: 2022: 1; 2023: 0; 2024: 2; 2025: 0; 2026: 1.
4 papers.
- 2024Translate-Distill: Learning Cross-Language Dense Retrieval by Translation and Distillationcited by 22
- 2022Neural Approaches to Multilingual Information Retrievalcited by 18
- 2024HLTCOE at TREC 2023 NeuCLIR Trackcited by 1
- 2026RoutIR: Fast Serving of Retrieval Pipelines for Retrieval-Augmented Generationcited by 1
- 2026RoutIR: Fast Serving of Retrieval Pipelines for Retrieval-Augmented Generation15 Jan 2026
- 2024HLTCOE at TREC 2023 NeuCLIR Track11 Apr 2024
- 2024Translate-Distill: Learning Cross-Language Dense Retrieval by Translation and Distillation9 Jan 2024
- 2022Neural Approaches to Multilingual Information Retrieval3 Sep 2022