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End-to-End Training of Neural Retrievers for Open-Domain Question Answering.

, , , , , , and . ACL/IJCNLP (1), page 6648-6662. Association for Computational Linguistics, (2021)

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Class Vectors: Embedding representation of Document Classes., and . CoRR, (2015)End-to-End Training of Multi-Document Reader and Retriever for Open-Domain Question Answering., , , , and . NeurIPS, page 25968-25981. (2021)Adaptive Methods for Nonconvex Optimization., , , , and . NeurIPS, page 9815-9825. (2018)Sports Video Classification from Multimodal Information Using Deep Neural Networks., , and . AAAI Fall Symposia, AAAI Press, (2013)Texar: A Modularized, Versatile, and Extensible Toolkit for Text Generation., , , , , , , , , and 6 other author(s). CoRR, (2018)Questions Are All You Need to Train a Dense Passage Retriever., , , , , and . CoRR, (2022)XNMT: The eXtensible Neural Machine Translation Toolkit., , , , , , , , , and 3 other author(s). AMTA (1), page 185-192. Association for Machine Translation in the Americas, (2018)Effective Use of Bidirectional Language Modeling for Medical Named Entity Recognition., , and . CoRR, (2017)Stronger Transformers for Neural Multi-Hop Question Generation., , , and . CoRR, (2020)Do Syntax Trees Help Pre-trained Transformers Extract Information?, , , and . CoRR, (2020)