---
title: "Who cites Learning Dense Representations of Phrases at Scale"
description: "58 papers of the Elamur Research library cite «Learning Dense Representations of Phrases at Scale», found in their bibliographies; the most…"
canonical: "https://research.elamur.ai/free/en/papers/lee-2021-learning-dense-representations-phrases-scale/cited-by/"
---
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# Who cites «Learning Dense Representations of Phrases at Scale»

58 papers of our library cite it (of the 141,840 whose bibliographies we read) · 6 with a page here, the most cited first · [← back to «Learning Dense Representations of Phrases at Scale»](https://md.research.elamur.ai/free/en/papers/lee-2021-learning-dense-representations-phrases-scale/)

1. [**Text Embeddings by Weakly-Supervised Contrastive Pre-training arXiv:2212.03533**Liang Wang, Nan Yang, Xiaolong Huang, et al.*2022 · 594 citations*](https://md.research.elamur.ai/free/en/papers/wang-2022-text-embeddings-weakly-supervised-contrastive/)
2. **[ColBERTv2: Effective and Efficient Retrieval via Lightweight Late Interaction](https://md.research.elamur.ai/free/en/papers/santhanam-2022-colbertv2-effective-efficient-retrieval-lightweight/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Keshav Santhanam, Omar Khattab, Jon Saad-Falcon, et al.*2022 · 477 citations*
3. **[PAQ: 65 Million Probably-Asked Questions and What You Can Do With Them](https://md.research.elamur.ai/free/en/papers/lewis-2021-paq-65-million-probably-asked/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Patrick Lewis, Yuxiang Wu, Linqing Liu, et al.*2021 · 286 citations*
4. **[Re2G: Retrieve, Rerank, Generate](https://md.research.elamur.ai/free/en/papers/glass-2022-re2g-retrieve-rerank-generate/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Michael Glass, Gaetano Rossiello, Md Faisal Mahbub Chowdhury, et al.*2022 · 183 citations*
5. **[Simple Entity-Centric Questions Challenge Dense Retrievers](https://md.research.elamur.ai/free/en/papers/sciavolino-2021-simple-entity-centric-questions-challenge/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Christopher Sciavolino, Zexuan Zhong, Jinhyuk Lee, et al.*2021 · 168 citations*
6. [**Gecko: Versatile Text Embeddings Distilled from Large Language Models arXiv:2403.20327**Jinhyuk Lee, Zhuyun Dai, Xiaoqi Ren, et al.*2024 · 72 citations*](https://md.research.elamur.ai/free/en/papers/lee-2024-gecko-versatile-text-embeddings-distilled/)

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

- [← back to](https://md.research.elamur.ai/free/en/papers/lee-2021-learning-dense-representations-phrases-scale/) — Learning Dense Representations of Phrases at Scale