---
title: "Who cites Platypus: Quick, Cheap, and — 100 citing papers"
description: "100 papers of the Elamur Research library cite «Platypus: Quick, Cheap, and Powerful Refinement of LLMs», found in their bibliographies…"
canonical: "https://research.elamur.ai/free/en/papers/lee-2023-platypus-quick-cheap-powerful-refinement/cited-by/"
---
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[home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Platypus: Quick, Cheap, and Powerful Refinement…](https://md.research.elamur.ai/free/en/papers/lee-2023-platypus-quick-cheap-powerful-refinement/) / cited by

# Who cites «Platypus: Quick, Cheap, and Powerful Refinement of LLMs»

100 papers of our library cite it (of the 149,439 whose bibliographies we read) · 26 with a page here, the most cited first · [← back to «Platypus: Quick, Cheap, and Powerful Refinement of LLMs»](https://md.research.elamur.ai/free/en/papers/lee-2023-platypus-quick-cheap-powerful-refinement/)

1. **[Siren's Song in the AI Ocean: A Survey on Hallucination in Large Language Models](https://md.research.elamur.ai/free/en/papers/zhang-2023-siren-s-song-ai-ocean/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Yue Zhang, Yafu Li, Leyang Cui, et al.*2023 · 977 citations*
2. [**MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models arXiv:2309.12284**Longhui Yu, Weisen Jiang, Han Shi, et al.*2023 · 565 citations*](https://md.research.elamur.ai/free/en/papers/yu-2023-metamath-bootstrap-your-own-mathematical/)
3. [**MAmmoTH: Building Math Generalist Models through Hybrid Instruction Tuning arXiv:2309.05653**Xiang Yue, Xingwei Qu, Ge Zhang, et al.*2023 · 295 citations*](https://md.research.elamur.ai/free/en/papers/yue-2023-mammoth-building-math-generalist-models/)
4. [**ToRA: A Tool-Integrated Reasoning Agent for Mathematical Problem Solving arXiv:2309.17452**Zhibin Gou, Zhihong Shao, Yeyun Gong, et al.*2023 · 225 citations*](https://md.research.elamur.ai/free/en/papers/gou-2023-tora-tool-integrated-reasoning-agent/)
5. **[InjecAgent: Benchmarking Indirect Prompt Injections in Tool-Integrated Large Language Model Agents](https://md.research.elamur.ai/free/en/papers/zhan-2024-injecagent-benchmarking-indirect-prompt-injections/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Qiusi Zhan, Zhixiang Liang, Zifan Ying, et al.*2024 · 193 citations*
6. [**The Unlocking Spell on Base LLMs: Rethinking Alignment via In-Context Learning arXiv:2312.01552**Bill Yuchen Lin, Abhilasha Ravichander, Ximing Lu, et al.*2023 · 150 citations*](https://md.research.elamur.ai/free/en/papers/lin-2023-unlocking-spell-base-llms-rethinking/)
7. [**Detecting Language Model Attacks with Perplexity arXiv:2308.14132**Gabriel Alon, Michael Kamfonas*2023 · 141 citations*](https://md.research.elamur.ai/free/en/papers/alon-2023-detecting-language-model-attacks-perplexity/)
8. [**Nemotron-4 340B Technical Report arXiv:2406.11704**Nvidia: Bo Adler, Niket Agarwal, Ashwath Aithal, et al.*2024 · 107 citations*](https://md.research.elamur.ai/free/en/papers/adler-2024-nemotron-4-340b-technical-report/)
9. [**Rethinking Benchmark and Contamination for Language Models with Rephrased Samples arXiv:2311.04850**Shuo Yang, Wei-Lin Chiang, Lianmin Zheng, et al.*2023 · 103 citations*](https://md.research.elamur.ai/free/en/papers/yang-2023-rethinking-benchmark-contamination-language-models/)
10. [**SeaLLMs — Large Language Models for Southeast Asia arXiv:2312.00738**Xuan-Phi Nguyen, Wenxuan Zhang, Xin Li, et al.*2023 · 92 citations*](https://md.research.elamur.ai/free/en/papers/nguyen-2023-seallms-large-language-models-southeast/)
11. [**Benchmark Data Contamination of Large Language Models: A Survey arXiv:2406.04244**Cheng Xu, Shuhao Guan, Derek Greene, et al.*2024 · 85 citations*](https://md.research.elamur.ai/free/en/papers/xu-2024-benchmark-data-contamination-large/)
12. [**Knowledge Fusion of Large Language Models arXiv:2401.10491**Fanqi Wan, Xinting Huang, Deng Cai, et al.*2024 · 82 citations*](https://md.research.elamur.ai/free/en/papers/wan-2024-knowledge-fusion-large-language-models/)
13. [**The Unreasonable Ineffectiveness of the Deeper Layers arXiv:2403.17887**Andrey Gromov, Kushal Tirumala, Hassan Shapourian, et al.*2024 · 71 citations*](https://md.research.elamur.ai/free/en/papers/gromov-2024-unreasonable-ineffectiveness-deeper-layers/)
14. **[Word Embeddings Are Steers for Language Models](https://md.research.elamur.ai/free/en/papers/han-2024-word-embeddings-are-steers-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Chi Han, Jialiang Xu, Manling Li, et al.*2024 · 49 citations*
15. [**GLoRe: When, Where, and How to Improve LLM Reasoning via Global and Local Refinements arXiv:2402.10963**Alex Havrilla, Sharath Raparthy, Christoforus Nalmpantis, et al.*2024 · 45 citations*](https://md.research.elamur.ai/free/en/papers/havrilla-2024-glore-where-improve-llm-reasoning/)
16. [**JetMoE: Reaching Llama2 Performance with 0.1M Dollars arXiv:2404.07413**Yikang Shen, Zhen Guo, Tianle Cai, et al.*2024 · 28 citations*](https://md.research.elamur.ai/free/en/papers/shen-2024-jetmoe-reaching-llama2-performance-0/)
17. **[Peacock: A Family of Arabic Multimodal Large Language Models and Benchmarks](https://md.research.elamur.ai/free/en/papers/alwajih-2024-peacock-family-arabic-multimodal-large/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Fakhraddin Alwajih, El Moatez Billah Nagoudi, Gagan Bhatia, et al.*2024 · 28 citations*
18. **[“Give Me BF16 or Give Me Death”? Accuracy-Performance Trade-Offs in LLM Quantization](https://md.research.elamur.ai/free/en/papers/kurtic-2025-give-me-bf16-or-give/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Eldar Kurtic, Alexandre Noll Marques, Shubhra Pandit, et al.*2025 · 21 citations*
19. [**Orion-14B: Open-source Multilingual Large Language Models arXiv:2401.12246**Du Chen, Yi Huang, Xiaopu Li, et al.*2024 · 17 citations*](https://md.research.elamur.ai/free/en/papers/chen-2024-orion-14b-open-source/)
20. **[Auto-Arena: Automating LLM Evaluations with Agent Peer Battles and Committee Discussions](https://md.research.elamur.ai/free/en/papers/zhao-2025-auto-arena-automating-llm-evaluations/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ruochen Zhao, Wenxuan Zhang, Yew Ken Chia, et al.*2025 · 16 citations*
21. [**VinaLLaMA: LLaMA-based Vietnamese Foundation Model arXiv:2312.11011**Quan Nguyen, Huy Pham, Dung Dao*2023 · 16 citations*](https://md.research.elamur.ai/free/en/papers/nguyen-2023-vinallama-llama-based-vietnamese-foundation/)
22. [**LLaSA: A Sensor-Aware LLM for Natural Language Reasoning of Human Activity from IMU Data arXiv:2406.14498**Sheikh Asif Imran, Mohammad Nur Hossain Khan, Subrata Biswas, et al.*2024 · 11 citations*](https://md.research.elamur.ai/free/en/papers/imran-2024-llasa-sensor-aware-llm-natural/)
23. **[HyperAdaLoRA: Accelerating LoRA Rank Allocation During Training via Hypernetworks without Sacrificing Performance](https://md.research.elamur.ai/free/en/papers/zhang-2026-hyperadalora-accelerating-lora-rank-allocation/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Hao Zhang, Zhenjia Li, Yifan Gao, et al.*2026 · 5 citations*
24. **[Not All Directions Matter: Towards Structured and Task-Aware Low-Rank Model Adaptation](https://md.research.elamur.ai/free/en/papers/xiao-2026-not-all-directions-matter-structured/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xi Xiao, Chenrui Ma, Yunbei Zhang, et al.*2026 · 3 citations*
25. **[SCAN: Structured Capability Assessment and Navigation for LLMs](https://md.research.elamur.ai/free/en/papers/wang-2026-scan-structured-capability-assessment-navigation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zongqi Wang, Tianle Gu, Chen Gong, et al.*2026 · 1 citation*
26. **[User-Assistant Bias in LLMs](https://md.research.elamur.ai/free/en/papers/pan-2026-user-assistant-bias-llms/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xu Pan, Jingxuan Fan, Zidi Xiong, et al.*2026*

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

- [← back to](https://md.research.elamur.ai/free/en/papers/lee-2023-platypus-quick-cheap-powerful-refinement/) — Platypus: Quick, Cheap, and Powerful Refinement of LLMs