🔗 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»

1. Is ChatGPT Good at Search? Investigating Large Language Models as Re-Ranking AgentsConference on Empirical Methods in Natural Language Processing (EMNLP)Weiwei Sun, Lingyong Yan, Xinyu Ma, et al.2023 · 496 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. SGPT: GPT Sentence Embeddings for Semantic SearcharXiv:2202.08904Niklas Muennighoff2022 · 189 citations
4. A Comprehensive Survey of Small Language Models in the Era of Large Language Models: Techniques, Enhancements, Applications, Collaboration with LLMs, and TrustworthinessACM Transactions on Intelligent Systems and TechnologyFali Wang, Zhiwei Zhang, Xianren Zhang, et al.2024 · 159 citations
5. Gecko: Versatile Text Embeddings Distilled from Large Language ModelsarXiv:2403.20327Jinhyuk Lee, Zhuyun Dai, Xiaoqi Ren, et al.2024 · 74 citations
6. RaDeR: Reasoning-aware Dense Retrieval ModelsConference on Empirical Methods in Natural Language Processing (EMNLP)Debrup Das, Sam O'Nuallain, Razieh Rahimi2025 · 14 citations
7. DRAMA: Diverse Augmentation from Large Language Models to Smaller Dense RetrieversAnnual Meeting of the Association for Computational Linguistics (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 DataWorkshop on Language Models for Low-Resource LanguagesZaruhi Navasardyan, Bagratuni Minsayan, Spartak Bughdaryan, et al.2026 · 3 citations
9. Improving Dialogue Act Recognition with Augmented DataWorkshop on Generation, Evaluation and Metrics (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.

This page in Markdown → https://md.research.elamur.ai/free/en/papers/bonifacio-2022-inpars-data-augmentation-information-retrieval/cited-by/