---
title: "Who cites LoRA-drop: Efficient LoRA — 10 citing papers"
description: "10 papers of the Elamur Research library cite «LoRA-drop: Efficient LoRA Parameter Pruning based on Output Evaluation», found in their…"
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# Who cites «LoRA-drop: Efficient LoRA Parameter Pruning based on Output Evaluation»

10 papers of our library cite it (of the 149,439 whose bibliographies we read) · 4 with a page here, the most cited first · [← back to «LoRA-drop: Efficient LoRA Parameter Pruning based on Output Evaluation»](https://md.research.elamur.ai/free/en/papers/zhou-2025-lora-drop-efficient-lora-parameter/)

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. **[LeLoRA: Learnable Low-Rank Adaptation of Large Language Models](https://md.research.elamur.ai/free/en/papers/zhou-2026-lelora-learnable-low-rank-adaptation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xiaoling Zhou, Mingjie Zhang, Zhemg Lee, et al.*2026*
3. **[RanLoRA: Residual-aware Nonlinear Low-Rank Adaptation](https://md.research.elamur.ai/free/en/papers/luo-2026-ranlora-residual-aware-nonlinear-low/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xu Luo, Yongbin Liu, Chunping Ouyang, et al.*2026*
4. **[WeightLoRA: Keep Only Necessary Adapters](https://md.research.elamur.ai/free/en/papers/veprikov-2026-weightlora-keep-only-necessary-adapters/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Andrey Veprikov, Vladimir Solodkin, Zyl Alexander, et al.*2026*

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

- [← back to](https://md.research.elamur.ai/free/en/papers/zhou-2025-lora-drop-efficient-lora-parameter/) — LoRA-drop: Efficient LoRA Parameter Pruning based on Output Evaluation