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Webis at TREC 2022: Deep Learning and Health Misinformation.

, , , , , , , , , , and . TREC, volume 500-338 of NIST Special Publication, National Institute of Standards and Technology (NIST), (2022)

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Sentence Embeddings for Russian NLU., , , , and . CoRR, (2019)Data-driven models and computational tools for neurolinguistics: a language technology perspective., , , , and . CoRR, (2020)Can BERT eat RuCoLA? Topological Data Analysis to Explain., , and . CoRR, (2023)NEREL: A Russian Dataset with Nested Named Entities and Relations., , , , , , , , and . CoRR, (2021)Supervised and Unsupervised Evaluation of Synthetic Code-Switching., and . W-NUT@COLING, page 113-123. Association for Computational Linguistics, (2022)Boosting Zero-shot Cross-lingual Retrieval by Training on Artificially Code-Switched Data., , and . ACL (Findings), page 3096-3108. Association for Computational Linguistics, (2023)Word Sense Disambiguation for 158 Languages using Word Embeddings Only., , , , , , , , , and . LREC, page 5943-5952. European Language Resources Association, (2020)Evaluation of Sentence Embedding Models for Natural Language Understanding Problems in Russian., , , , and . AIST, volume 11832 of Lecture Notes in Computer Science, page 205-217. Springer, (2019)DaNetQA: A Yes/No Question Answering Dataset for the Russian Language., , , , , and . AIST, volume 12602 of Lecture Notes in Computer Science, page 57-68. Springer, (2020)Single Example Can Improve Zero-Shot Data Generation., , , , and . INLG, page 201-211. Association for Computational Linguistics, (2021)