--- title: "Who cites RoCoFT: Efficient Finetuning of — 4 citing papers" description: "4 papers of the Elamur Research library cite «RoCoFT: Efficient Finetuning of Large Language Models with Row-Column Updates», found in their…" canonical: "https://research.elamur.ai/free/en/papers/kowsher-2025-rocoft-efficient-finetuning-large-language/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/kowsher-2025-rocoft-efficient-finetuning-large-language/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [RoCoFT: Efficient Finetuning of Large Language…](https://md.research.elamur.ai/free/en/papers/kowsher-2025-rocoft-efficient-finetuning-large-language/) / cited by # Who cites «RoCoFT: Efficient Finetuning of Large Language Models with Row-Column Updates» 4 papers of our library cite it (of the 149,439 whose bibliographies we read) · 2 with a page here, the most cited first · [← back to «RoCoFT: Efficient Finetuning of Large Language Models with Row-Column Updates»](https://md.research.elamur.ai/free/en/papers/kowsher-2025-rocoft-efficient-finetuning-large-language/) 1. [**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/) 2. **[Localized Low-Rank Adaptation within Clustered Parameter Subspaces](https://md.research.elamur.ai/free/en/papers/xiong-2026-localized-low-rank-adaptation-within/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jiahao Xiong, Yihe Liu, Xianming Hu, et al.*2026* 2 more papers of our library cite it; they have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/papers/kowsher-2025-rocoft-efficient-finetuning-large-language/) — RoCoFT: Efficient Finetuning of Large Language Models with Row-Column Updates