--- title: "Who cites Parameter-Efficient Fine-Tuning Design Spaces" description: "31 papers of the Elamur Research library cite «Parameter-Efficient Fine-Tuning Design Spaces», found in their bibliographies; the most cited first." canonical: "https://research.elamur.ai/free/en/papers/chen-2023-parameter-efficient-fine-tuning-design/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/chen-2023-parameter-efficient-fine-tuning-design/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Parameter-Efficient Fine-Tuning Design Spaces](https://md.research.elamur.ai/free/en/papers/chen-2023-parameter-efficient-fine-tuning-design/) / cited by # Who cites «Parameter-Efficient Fine-Tuning Design Spaces» 31 papers of our library cite it (of the 149,439 whose bibliographies we read) · 12 with a page here, the most cited first · [← back to «Parameter-Efficient Fine-Tuning Design Spaces»](https://md.research.elamur.ai/free/en/papers/chen-2023-parameter-efficient-fine-tuning-design/) 1. **[LLM-Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of Large Language Models](https://md.research.elamur.ai/free/en/papers/hu-2023-llm-adapters-adapter-family-parameter/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Zhiqiang Hu, Lei Wang, Yihuai Lan, et al.*2023 · 401 citations* 2. [**Parameter-Efficient Fine-Tuning for Large Models: A Comprehensive Survey arXiv:2403.14608**Zeyu Han, Chao Gao, Jinyang Liu, et al.*2024 · 240 citations*](https://md.research.elamur.ai/free/en/papers/han-2024-parameter-efficient-fine-tuning-large/) 3. [**Aligning Large Language Models with Human: A Survey arXiv:2307.12966**Yufei Wang, Wanjun Zhong, Liangyou Li, et al.*2023 · 202 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-aligning-large-language-models-human/) 4. [**Scaling Down to Scale Up: A Guide to Parameter-Efficient Fine-Tuning arXiv:2303.15647**Vladislav Lialin, Vijeta Deshpande, Xiaowei Yao, et al.*2023 · 129 citations*](https://md.research.elamur.ai/free/en/papers/lialin-2023-scaling-down-scale-up-guide/) 5. **[Unlearn What You Want to Forget: Efficient Unlearning for LLMs](https://md.research.elamur.ai/free/en/papers/chen-2023-unlearn-what-you-want-forget/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Jiaao Chen, Diyi Yang*2023 · 124 citations* 6. [**Pushing Mixture of Experts to the Limit: Extremely Parameter Efficient MoE for Instruction Tuning arXiv:2309.05444**Ted Zadouri, Ahmet Ustun, Arash Ahmadian, et al.*2023 · 69 citations*](https://md.research.elamur.ai/free/en/papers/zadouri-2023-pushing-mixture-experts-limit-extremely/) 7. **[AutoPEFT: Automatic Configuration Search for Parameter-Efficient Fine-Tuning](https://md.research.elamur.ai/free/en/papers/zhou-2024-autopeft-automatic-configuration-search-parameter/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Han Zhou, Xingchen Wan, Ivan Vulić, et al.*2024 · 46 citations* 8. **[Fine-tuning Large Language Models with Limited Data: A Survey and Practical Guide](https://md.research.elamur.ai/free/en/papers/szep-2026-fine-tuning-large-language-models/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Marton Szep, Daniel Rueckert, Rüdiger von Eisenhart-Rothe, et al.*2026 · 7 citations* 9. **[CUFE at StanceEval2024: Arabic Stance Detection with Fine-Tuned Llama-3 Model](https://md.research.elamur.ai/free/en/papers/ibrahim-2024-cufe-stanceeval2024-arabic-stance-detection/) [Arabic Natural Language Processing Conference (ArabicNLP)](https://md.research.elamur.ai/free/en/venues/arabicnlp/)**Michael Ibrahim*2024 · 4 citations* 10. **[CUFE at NADI 2024 shared task: Fine-Tuning Llama-3 To Translate From Arabic Dialects To Modern Standard Arabic](https://md.research.elamur.ai/free/en/papers/ibrahim-2024-cufe-nadi-2024-shared-task/) [Arabic Natural Language Processing Conference (ArabicNLP)](https://md.research.elamur.ai/free/en/venues/arabicnlp/)**Michael Ibrahim*2024 · 2 citations* 11. [**A Survey on Parameter-efficient Fine-tuning of Large Models: Techniques, Trends, and Challenges (大模型参数高效微调方法综述: 技术、趋势与挑战) Acta Automatica Sinica (自动化学报)**Anda Tang (唐岸达), Zhouchen Lin (林宙辰)*2026*](https://md.research.elamur.ai/free/en/papers/tang-2026-parameter-efficient-fine/) 12. **[Look Within or Beyond? A Theoretical Comparison Between Parameter-Efficient and Full Fine-Tuning](https://md.research.elamur.ai/free/en/papers/liu-2026-look-within-or-beyond-theoretical/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**YongKang Liu, Xingle Xu, Ercong Nie, et al.*2026* 19 more papers of our library cite it; they have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/papers/chen-2023-parameter-efficient-fine-tuning-design/) — Parameter-Efficient Fine-Tuning Design Spaces