---
title: "Who cites QAmeleon: Multilingual QA with Only 5 Examples"
description: "29 papers of the Elamur Research library cite «QAmeleon: Multilingual QA with Only 5 Examples», found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/papers/agrawal-2023-qameleon-multilingual-qa-only-5/cited-by/"
---
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[home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [QAmeleon: Multilingual QA with Only 5 Examples](https://md.research.elamur.ai/free/en/papers/agrawal-2023-qameleon-multilingual-qa-only-5/) / cited by

# Who cites «QAmeleon: Multilingual QA with Only 5 Examples»

29 papers of our library cite it (of the 149,439 whose bibliographies we read) · 8 with a page here, the most cited first · [← back to «QAmeleon: Multilingual QA with Only 5 Examples»](https://md.research.elamur.ai/free/en/papers/agrawal-2023-qameleon-multilingual-qa-only-5/)

1. **[Distilling Step-by-Step! Outperforming Larger Language Models with Less Training Data and Smaller Model Sizes](https://md.research.elamur.ai/free/en/papers/hsieh-2023-distilling-step-step-outperforming-larger/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Cheng-Yu Hsieh, Chun-Liang Li, Chih-kuan Yeh, et al.*2023 · 690 citations*
2. **[Unnatural Instructions: Tuning Language Models with (Almost) No Human Labor](https://md.research.elamur.ai/free/en/papers/honovich-2023-unnatural-instructions-tuning-language-models/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Or Honovich, Thomas Scialom, Omer Levy, et al.*2023 · 366 citations*
3. [**Challenges and Applications of Large Language Models arXiv:2307.10169**Jean Kaddour, Joshua Harris, Maximilian Mozes, et al.*2023 · 301 citations*](https://md.research.elamur.ai/free/en/papers/kaddour-2023-challenges-applications-large-language-models/)
4. [**ToolAlpaca: Generalized Tool Learning for Language Models with 3000 Simulated Cases arXiv:2306.05301**Qiaoyu Tang, Ziliang Deng, Hongyu Lin, et al.*2023 · 180 citations*](https://md.research.elamur.ai/free/en/papers/tang-2023-toolalpaca-generalized-tool-learning-language/)
5. **[TrueTeacher: Learning Factual Consistency Evaluation with Large Language Models](https://md.research.elamur.ai/free/en/papers/gekhman-2023-trueteacher-learning-factual-consistency-evaluation/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Zorik Gekhman, Jonathan Herzig, Roee Aharoni, et al.*2023 · 106 citations*
6. **[BUFFET: Benchmarking Large Language Models for Few-shot Cross-lingual Transfer](https://md.research.elamur.ai/free/en/papers/asai-2024-buffet-benchmarking-large-language-models/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Akari Asai, Sneha Kudugunta, Xinyan Yu, et al.*2024 · 86 citations*
7. [**Multilingual Large Language Model: A Survey of Resources, Taxonomy and Frontiers arXiv:2404.04925**Libo Qin, Qiguang Chen, Yuhang Zhou, et al.*2024 · 75 citations*](https://md.research.elamur.ai/free/en/papers/qin-2024-multilingual-large-language-model-survey/)
8. [**EDRAC: Benchmarking Arabic Dialect Reading Comprehension arXiv:2609.01113**Noor Abo Mokh, Kirill Chirkunov, Teresa Lynn, et al.*2026*](https://md.research.elamur.ai/free/en/papers/mokh-2026-edrac-benchmarking-arabic-dialect-reading/)

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

- [← back to](https://md.research.elamur.ai/free/en/papers/agrawal-2023-qameleon-multilingual-qa-only-5/) — QAmeleon: Multilingual QA with Only 5 Examples