ICML "parameter-efficient fine-tuning" Papers
17 papers found
APT: Adaptive Pruning and Tuning Pretrained Language Models for Efficient Training and Inference
Bowen Zhao, Hannaneh Hajishirzi, Qingqing Cao
ICML 2024poster
Asymmetry in Low-Rank Adapters of Foundation Models
Jiacheng Zhu, Kristjan Greenewald, Kimia Nadjahi et al.
ICML 2024poster
DoRA: Weight-Decomposed Low-Rank Adaptation
Shih-Yang Liu, Chien-Yi Wang, Hongxu Yin et al.
ICML 2024poster
Exploring Training on Heterogeneous Data with Mixture of Low-rank Adapters
Yuhang Zhou, Zhao Zihua, Siyuan Du et al.
ICML 2024poster
From Yes-Men to Truth-Tellers: Addressing Sycophancy in Large Language Models with Pinpoint Tuning
Wei Chen, Zhen Huang, Liang Xie et al.
ICML 2024poster
Learning to Route Among Specialized Experts for Zero-Shot Generalization
Mohammed Muqeeth, Haokun Liu, Yufan Liu et al.
ICML 2024poster
LoRA Training in the NTK Regime has No Spurious Local Minima
Uijeong Jang, Jason Lee, Ernest Ryu
ICML 2024poster
Memory-Space Visual Prompting for Efficient Vision-Language Fine-Tuning
Shibo Jie, Yehui Tang, Ning Ding et al.
ICML 2024poster
Model Tailor: Mitigating Catastrophic Forgetting in Multi-modal Large Language Models
Didi Zhu, Zhongyi Sun, Zexi Li et al.
ICML 2024poster
Open-Vocabulary Calibration for Fine-tuned CLIP
Shuoyuan Wang, Jindong Wang, Guoqing Wang et al.
ICML 2024poster
Parameter-Efficient Fine-Tuning with Controls
Chi Zhang, Jingpu Cheng, Yanyu Xu et al.
ICML 2024poster
Parameter-Efficient Fine-Tuning with Discrete Fourier Transform
Ziqi Gao, Qichao Wang, Aochuan Chen et al.
ICML 2024poster
Riemannian Preconditioned LoRA for Fine-Tuning Foundation Models
Fangzhao Zhang, Mert Pilanci
ICML 2024poster
RoSA: Accurate Parameter-Efficient Fine-Tuning via Robust Adaptation
Mahdi Nikdan, Soroush Tabesh, Elvir Crnčević et al.
ICML 2024poster
SAM-E: Leveraging Visual Foundation Model with Sequence Imitation for Embodied Manipulation
Junjie Zhang, Chenjia Bai, Haoran He et al.
ICML 2024poster
SPP: Sparsity-Preserved Parameter-Efficient Fine-Tuning for Large Language Models
Xudong LU, Aojun Zhou, Yuhui Xu et al.
ICML 2024poster
Unleashing the Power of Meta-tuning for Few-shot Generalization Through Sparse Interpolated Experts
Shengzhuang Chen, Jihoon Tack, Yunqiao Yang et al.
ICML 2024poster