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MLQA: Evaluating Cross-lingual Extractive Question Answering

, , , , and . (2019)cite arxiv:1910.07475Comment: To appear in ACL 2020.

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MLQA: Evaluating Cross-lingual Extractive Question Answering, , , , and . (2019)cite arxiv:1910.07475Comment: To appear in ACL 2020.Dense Passage Retrieval for Open-Domain Question Answering, , , , , , , and . (2020)cite arxiv:2004.04906Comment: EMNLP 2020.Compressing a long range dependent renewal process., and . ISIT, page 1443-1447. IEEE, (2010)Domain-matched Pre-training Tasks for Dense Retrieval., , , , , , , , , and 1 other author(s). NAACL-HLT (Findings), page 1524-1534. Association for Computational Linguistics, (2022)Boosted Dense Retriever., , , , , and . NAACL-HLT, page 3102-3117. Association for Computational Linguistics, (2022)Bridging the Training-Inference Gap for Dense Phrase Retrieval., , , , , , and . EMNLP (Findings), page 3713-3724. Association for Computational Linguistics, (2022)CITADEL: Conditional Token Interaction via Dynamic Lexical Routing for Efficient and Effective Multi-Vector Retrieval., , , , , , , and . ACL (1), page 11891-11907. Association for Computational Linguistics, (2023)Joint Verification and Reranking for Open Fact Checking Over Tables., , , , , and . CoRR, (2020)CCQA: A New Web-Scale Question Answering Dataset for Model Pre-Training., , , , , , and . NAACL-HLT (Findings), page 2402-2420. Association for Computational Linguistics, (2022)Hierarchical Video-Moment Retrieval and Step-Captioning., , , , , , and . CVPR, page 23056-23065. IEEE, (2023)