"parameter-efficient finetuning" Papers
13 papers found
Conference
Continual Personalization for Diffusion Models
Yu-Chien Liao, Jr-Jen Chen, Chi-Pin Huang et al.
ICCV 2025arXiv:2510.02296
Curvature Tuning: Provable Training-free Model Steering From a Single Parameter
Leyang Hu, Matteo Gamba, Randall Balestriero
NEURIPS 2025arXiv:2502.07783
1
citations
Decoupling Angles and Strength in Low-rank Adaptation
Massimo Bini, Leander Girrbach, Zeynep Akata
ICLR 2025arXiv:2503.18225
8
citations
Latent Space Factorization in LoRA
Shashi Kumar, Yacouba Kaloga, John Mitros et al.
NEURIPS 2025arXiv:2510.19640
LoRA Done RITE: Robust Invariant Transformation Equilibration for LoRA Optimization
Jui-Nan Yen, Si Si, Zhao Meng et al.
ICLR 2025arXiv:2410.20625
16
citations
LoRA Learns Less and Forgets Less
Jonathan Frankle, Jose Javier Gonzalez Ortiz, Cody Blakeney et al.
ICLR 2025arXiv:2405.09673
252
citations
Pay Attention to Small Weights
chao zhou, Tom Jacobs, Advait Gadhikar et al.
NEURIPS 2025arXiv:2506.21374
The Unreasonable Ineffectiveness of the Deeper Layers
Andrey Gromov, Kushal Tirumala, Hassan Shapourian et al.
ICLR 2025arXiv:2403.17887
172
citations
Accurate LoRA-Finetuning Quantization of LLMs via Information Retention
Haotong Qin, Xudong Ma, Xingyu Zheng et al.
ICML 2024arXiv:2402.05445
74
citations
A Sober Look at LLMs for Material Discovery: Are They Actually Good for Bayesian Optimization Over Molecules?
Agustinus Kristiadi, Felix Strieth-Kalthoff, Marta Skreta et al.
ICML 2024arXiv:2402.05015
44
citations
ETHER: Efficient Finetuning of Large-Scale Models with Hyperplane Reflections
Massimo Bini, Karsten Roth, Zeynep Akata et al.
ICML 2024arXiv:2405.20271
9
citations
FedDAT: An Approach for Foundation Model Finetuning in Multi-Modal Heterogeneous Federated Learning
Haokun Chen, Yao Zhang, Denis Krompass et al.
AAAI 2024paperarXiv:2308.12305
86
citations
OneTracker: Unifying Visual Object Tracking with Foundation Models and Efficient Tuning
Lingyi Hong, Shilin Yan, Renrui Zhang et al.
CVPR 2024highlightarXiv:2403.09634
123
citations