🔗 Who cites «End-to-End Training of Neural Retrievers for Open-Domain Question Answering»

53 papers of our library cite it (of the 141,840 whose bibliographies we read) · 7 with a page here, the most cited first · ← back to «End-to-End Training of Neural Retrievers for Open-Domain Question Answering»

1. Improving the Domain Adaptation of Retrieval Augmented Generation (RAG) Models for Open Domain Question AnsweringShamane Siriwardhana, Rivindu Weerasekera, Elliott Wen, et al.2023 · 403 citations
2. Text and Code Embeddings by Contrastive Pre-TrainingArvind Neelakantan, Tao Xu, Raul Puri, et al.2022 · 319 citations
3. Large Dual Encoders Are Generalizable RetrieversJianmo Ni, Chen Qu, Jing Lu, et al.2021 · 276 citations
4. RocketQAv2: A Joint Training Method for Dense Passage Retrieval and Passage Re-rankingRuiyang Ren, Yingqi Qu, Jing Liu, et al.2021 · 256 citations
5. Improving Passage Retrieval with Zero-Shot Question GenerationDevendra Sachan, Mike Lewis, Mandar Joshi, et al.2022 · 197 citations
6. Dense X Retrieval: What Retrieval Granularity Should We Use?Tong Chen, Hongwei Wang, Sihao Chen, et al.2024 · 142 citations
7. KG-FiD: Infusing Knowledge Graph in Fusion-in-Decoder for Open-Domain Question AnsweringDonghan Yu, Chenguang Zhu, Yuwei Fang, et al.2022 · 115 citations

46 more papers of our library cite it; they have no page here yet.

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