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Who cites «Questions Are All You Need to Train a Dense Passage Retriever»

36 papers of our library cite it (of the 149,439 whose bibliographies we read) · 10 with a page here, the most cited first · ← back to «Questions Are All You Need to Train a Dense Passage Retriever»

  1. REPLUG: Retrieval-Augmented Black-Box Language ModelsarXiv:2301.12652Weijia Shi, Sewon Min, Michihiro Yasunaga, et al.2023 · 492 citations
  2. Large Language Models for Information Retrieval: A SurveyACM Transactions on Information SystemsYutao Zhu; Huaying Yuan; Shuting Wang; Jiongnan Liu; Wenhan Liu; Chenlong Deng; Haonan Chen; Zheng Liu; Zhicheng Dou;, Ji-Rong Wen2023 · 339 citations
  3. Generate rather than Retrieve: Large Language Models are Strong Context GeneratorsarXiv:2209.10063Wenhao Yu, Dan Iter, Shuohang Wang, et al.2022 · 281 citations
  4. RAPTOR: Recursive Abstractive Processing for Tree-Organized RetrievalarXiv:2401.18059Parth Sarthi, Salman Abdullah, Aditi Tuli, et al.2024 · 193 citations
  5. RankVicuna: Zero-Shot Listwise Document Reranking with Open-Source Large Language ModelsarXiv:2309.15088Ronak Pradeep, Sahel Sharifymoghaddam, Jimmy Lin2023 · 81 citations
  6. Gecko: Versatile Text Embeddings Distilled from Large Language ModelsarXiv:2403.20327Jinhyuk Lee, Zhuyun Dai, Xiaoqi Ren, et al.2024 · 74 citations
  7. Improving Language Models via Plug-and-Play Retrieval FeedbackarXiv:2305.14002Wenhao Yu, Zhihan Zhang, Zhenwen Liang, et al.2023 · 54 citations
  8. IfQA: A Dataset for Open-domain Question Answering under Counterfactual PresuppositionsWenhao Yu, Meng Jiang, Peter Clark, et al.2023 · 26 citations

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

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