---
title: "Who cites InPars: Data Augmentation for — 53 citing papers"
description: "53 papers of the Elamur Research library cite «InPars: Data Augmentation for Information Retrieval using Large Language Models», found in their…"
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---
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[home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [InPars: Data Augmentation for Information…](https://md.research.elamur.ai/free/en/papers/bonifacio-2022-inpars-data-augmentation-information-retrieval/) / cited by

# Who cites «InPars: Data Augmentation for Information Retrieval using Large Language Models»

53 papers of our library cite it (of the 149,439 whose bibliographies we read) · 9 with a page here, the most cited first · [← back to «InPars: Data Augmentation for Information Retrieval using Large Language Models»](https://md.research.elamur.ai/free/en/papers/bonifacio-2022-inpars-data-augmentation-information-retrieval/)

1. **[Is ChatGPT Good at Search? Investigating Large Language Models as Re-Ranking Agents](https://md.research.elamur.ai/free/en/papers/sun-2023-chatgpt-good-search-investigating-large/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Weiwei Sun, Lingyong Yan, Xinyu Ma, et al.*2023 · 496 citations*
2. **[Large Language Models for Information Retrieval: A Survey](https://md.research.elamur.ai/free/en/papers/zhu-2023-large-language-models-information-retrieval/) [ACM Transactions on Information Systems](https://md.research.elamur.ai/free/en/venues/acm-transactions-on-information-systems/)**Yutao Zhu; Huaying Yuan; Shuting Wang; Jiongnan Liu; Wenhan Liu; Chenlong Deng; Haonan Chen; Zheng Liu; Zhicheng Dou;, Ji-Rong Wen*2023 · 339 citations*
3. [**SGPT: GPT Sentence Embeddings for Semantic Search arXiv:2202.08904**Niklas Muennighoff*2022 · 189 citations*](https://md.research.elamur.ai/free/en/papers/muennighoff-2022-sgpt-gpt-sentence-embeddings-semantic/)
4. **[A Comprehensive Survey of Small Language Models in the Era of Large Language Models: Techniques, Enhancements, Applications, Collaboration with LLMs, and Trustworthiness](https://md.research.elamur.ai/free/en/papers/wang-2024-comprehensive-survey-small-language-models/) [ACM Transactions on Intelligent Systems and Technology](https://md.research.elamur.ai/free/en/venues/acm-transactions-on-intelligent-systems-and-technology/)**Fali Wang, Zhiwei Zhang, Xianren Zhang, et al.*2024 · 159 citations*
5. [**Gecko: Versatile Text Embeddings Distilled from Large Language Models arXiv:2403.20327**Jinhyuk Lee, Zhuyun Dai, Xiaoqi Ren, et al.*2024 · 74 citations*](https://md.research.elamur.ai/free/en/papers/lee-2024-gecko-versatile-text-embeddings-distilled/)
6. **[RaDeR: Reasoning-aware Dense Retrieval Models](https://md.research.elamur.ai/free/en/papers/das-2025-rader-reasoning-aware-dense-retrieval/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Debrup Das, Sam O'Nuallain, Razieh Rahimi*2025 · 14 citations*
7. **[DRAMA: Diverse Augmentation from Large Language Models to Smaller Dense Retrievers](https://md.research.elamur.ai/free/en/papers/ma-2025-drama-diverse-augmentation-large-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xueguang Ma, Xi Victoria Lin, Barlas Oguz, et al.*2025 · 13 citations*
8. **[Less is More: Adapting Text Embeddings for Low-Resource Languages with Small Scale Noisy Synthetic Data](https://md.research.elamur.ai/free/en/papers/navasardyan-2026-less-is-more-adapting-text/) [Workshop on Language Models for Low-Resource Languages](https://md.research.elamur.ai/free/en/venues/loreslm/)**Zaruhi Navasardyan, Bagratuni Minsayan, Spartak Bughdaryan, et al.*2026 · 3 citations*
9. **[Improving Dialogue Act Recognition with Augmented Data](https://md.research.elamur.ai/free/en/papers/mahajan-2022-improving-dialogue-act-recognition-augmented/) [Workshop on Generation, Evaluation and Metrics (GEM)](https://md.research.elamur.ai/free/en/venues/gem/)**Khyati Mahajan, Soham Parikh, Quaizar Vohra, et al.*2022 · 2 citations*

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

- [← back to](https://md.research.elamur.ai/free/en/papers/bonifacio-2022-inpars-data-augmentation-information-retrieval/) — InPars: Data Augmentation for Information Retrieval using Large Language Models