Appeared in: Proceedings of the 32nd Text REtrieval Conference (TREC 2023)
Abstract:
The principal goal of the TREC Neural Cross-Language Information Retrieval (NeuCLIR) track is to study the impact of neural approaches to cross-language information retrieval. The track has created four collections, large collections of Chinese, Persian, and Russian newswire and a smaller collection of Chinese scientific abstracts. The principal tasks are ranked retrieval of news in one of the three languages, using English topics. Results for a multilingual task, also with English topics but with documents from all three newswire collections, are also reported. New in this second year of the track is a pilot technical documents CLIR task for ranked retrieval of Chinese technical documents using English topics. A total of 220 runs across all tasks were submitted by six participating teams and, as baselines, by track coordinators. Task descriptions and results are presented.
BibTeX @inproceedings{lawrie:trec2023-neuclir, author = {Lawrie, Dawn and MacAvaney, Sean and Mayfield, James and McNamee, Paul and Oard, Douglas and Soldaini, Luca and Yang, Eugene}, title = {Overview of the TREC 2023 NeuCLIR Track}, booktitle = {Proceedings of the 32nd Text REtrieval Conference}, year = {2023}, url = {https://arxiv.org/abs/2404.08071} }