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MLQA: Evaluating Cross-lingual Extractive Question Answering., , , , and . CoRR, (2019)Understanding and predicting disease relationships through similarity fusion., , , , and . Bioinform., 35 (7): 1213-1220 (2019)Answering Complex Open-Domain Questions with Multi-Hop Dense Retrieval., , , , , , , , , and 1 other author(s). CoRR, (2020)Challenges in Generalization in Open Domain Question Answering., , , and . CoRR, (2021)MultiContrievers: Analysis of Dense Retrieval Representations., , , and . CoRR, (2024)EditEval: An Instruction-Based Benchmark for Text Improvements., , , , , , , , and . CoRR, (2022)A Few More Examples May Be Worth Billions of Parameters., , , and . CoRR, (2021)Salient Phrase Aware Dense Retrieval: Can a Dense Retriever Imitate a Sparse One?, , , , , , , , and . EMNLP (Findings), page 250-262. Association for Computational Linguistics, (2022)A Few More Examples May Be Worth Billions of Parameters., , , and . EMNLP (Findings), page 1017-1029. Association for Computational Linguistics, (2022)Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks., , , , , , , , , and 2 other author(s). NeurIPS, (2020)