---
title: "Who cites LoraHub: Efficient Cross-Task — 95 citing papers"
description: "95 papers of the Elamur Research library cite «LoraHub: Efficient Cross-Task Generalization via Dynamic LoRA Composition», found in their…"
canonical: "https://research.elamur.ai/free/en/papers/huang-2023-lorahub-efficient-cross-task-generalization/cited-by/"
---
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[home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [LoraHub: Efficient Cross-Task Generalization via…](https://md.research.elamur.ai/free/en/papers/huang-2023-lorahub-efficient-cross-task-generalization/) / cited by

# Who cites «LoraHub: Efficient Cross-Task Generalization via Dynamic LoRA Composition»

95 papers of our library cite it (of the 141,840 whose bibliographies we read) · 4 with a page here, the most cited first · [← back to «LoraHub: Efficient Cross-Task Generalization via Dynamic LoRA Composition»](https://md.research.elamur.ai/free/en/papers/huang-2023-lorahub-efficient-cross-task-generalization/)

1. [**Parameter-Efficient Fine-Tuning for Large Models: A Comprehensive Survey arXiv:2403.14608**Zeyu Han, Chao Gao, Jinyang Liu, et al.*2024 · 236 citations*](https://md.research.elamur.ai/free/en/papers/han-2024-parameter-efficient-fine-tuning-large/)
2. [**Scaling Down to Scale Up: A Guide to Parameter-Efficient Fine-Tuning arXiv:2303.15647**Vladislav Lialin, Vijeta Deshpande, Xiaowei Yao, et al.*2023 · 128 citations*](https://md.research.elamur.ai/free/en/papers/lialin-2023-scaling-down-scale-up-guide/)
3. [**StyleRemix: Interpretable Authorship Obfuscation via Distillation and Perturbation of Style Elements**Jillian Fisher, Skyler Hallinan, Ximing Lu, et al.*2024 · 16 citations*](https://md.research.elamur.ai/free/en/papers/fisher-2024-styleremix-interpretable-authorship-obfuscation-distillation/)
4. [**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/)

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

- [← back to](https://md.research.elamur.ai/free/en/papers/huang-2023-lorahub-efficient-cross-task-generalization/) — LoraHub: Efficient Cross-Task Generalization via Dynamic LoRA Composition