  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.
