Papers
193 papers found
GBA: A Tuning-free Approach to Switch between Synchronous and Asynchronous Training for Recommendation Models
Wenbo Su, Yuanxing Zhang, Yufeng Cai et al.
Tuning-Free Generalized Hamiltonian Monte Carlo
Matthew D. Hoffman, Pavel Sountsov
TFPnP: Tuning-free Plug-and-Play Proximal Algorithms with Applications to Inverse Imaging Problems
Kaixuan Wei, Angelica Aviles-Rivero, Jingwei Liang et al.
P-Tuning: Prompt Tuning Can Be Comparable to Fine-tuning Across Scales and Tasks
Xiao Liu, Kaixuan Ji, Yicheng Fu et al.
Inducer-tuning: Connecting Prefix-tuning and Adapter-tuning
Yifan Chen, Devamanyu Hazarika, Mahdi Namazifar et al.
Singular Value Fine-tuning: Few-shot Segmentation requires Few-parameters Fine-tuning
Yanpeng Sun, Qiang Chen, Xiangyu He et al.
S4-Tuning: A Simple Cross-lingual Sub-network Tuning Method
Runxin Xu, Fuli Luo, Baobao Chang et al.
Prompt-Tuning Can Be Much Better Than Fine-Tuning on Cross-lingual Understanding With Multilingual Language Models
Lifu Tu, Caiming Xiong, Yingbo Zhou
Domain-Oriented Prefix-Tuning: Towards Efficient and Generalizable Fine-tuning for Zero-Shot Dialogue Summarization
Lulu Zhao, Fujia Zheng, Weihao Zeng et al.
Scaling & Shifting Your Features: A New Baseline for Efficient Model Tuning
Dongze Lian, Daquan Zhou, Jiashi Feng et al.
Syndicated Bandits: A Framework for Auto Tuning Hyper-parameters in Contextual Bandit Algorithms
QIN DING, Yue Kang, Yi-Wei Liu et al.
Controlled Sparsity via Constrained Optimization or: How I Learned to Stop Tuning Penalties and Love Constraints
Jose Gallego-Posada, Juan Ramirez, Akram Erraqabi et al.
Few-Shot Parameter-Efficient Fine-Tuning is Better and Cheaper than In-Context Learning
Haokun Liu, Derek Tam, Mohammed Muqeeth et al.
360-MLC: Multi-view Layout Consistency for Self-training and Hyper-parameter Tuning
Bolivar Solarte, Chin-Hsuan Wu, Yueh-Cheng Liu et al.
Sparse Structure Search for Delta Tuning
Shengding Hu, Zhen Zhang, Ning Ding et al.
FedAvg with Fine Tuning: Local Updates Lead to Representation Learning
Liam Collins, Hamed Hassani, Aryan Mokhtari et al.
LIFT: Language-Interfaced Fine-Tuning for Non-language Machine Learning Tasks
Tuan Dinh, Yuchen Zeng, Ruisu Zhang et al.
AD-DROP: Attribution-Driven Dropout for Robust Language Model Fine-Tuning
Tao Yang, JInghao Deng, Xiaojun Quan et al.
LST: Ladder Side-Tuning for Parameter and Memory Efficient Transfer Learning
Yi-Lin Sung, Jaemin Cho, Mohit Bansal
Test-Time Prompt Tuning for Zero-Shot Generalization in Vision-Language Models
Manli Shu, Weili Nie, De-An Huang et al.
P2P: Tuning Pre-trained Image Models for Point Cloud Analysis with Point-to-Pixel Prompting
Ziyi Wang, Xumin Yu, Yongming Rao et al.
Less-forgetting Multi-lingual Fine-tuning
Yuren Mao, Yaobo Liang, Nan Duan et al.
On Reinforcement Learning and Distribution Matching for Fine-Tuning Language Models with no Catastrophic Forgetting
Tomasz Korbak, Hady Elsahar, Germán Kruszewski et al.
Fine-tuning Language Models over Slow Networks using Activation Quantization with Guarantees
Jue WANG, Binhang Yuan, Luka Rimanic et al.