"fine-tuning" Papers
14 papers found
Conference
ArtiFade: Learning to Generate High-quality Subject from Blemished Images
Shuya Yang, Shaozhe Hao, Yukang Cao et al.
CVPR 2025arXiv:2409.03745
1
citations
CLIPPER: Compression enables long-context synthetic data generation
Chau Minh Pham, Yapei Chang, Mohit Iyyer
COLM 2025paperarXiv:2502.14854
2
citations
Hawkeye: Model Collaboration for Efficient Reasoning
Jianshu She, Zhuohao Li, Zhemin Huang et al.
COLM 2025paper
ParaPO: Aligning Language Models to Reduce Verbatim Reproduction of Pre-training Data
Tong Chen, Faeze Brahman, Jiacheng Liu et al.
COLM 2025paperarXiv:2504.14452
3
citations
Privately Learning from Graphs with Applications in Fine-tuning Large Language Models
Haoteng Yin, Rongzhe Wei, Eli Chien et al.
COLM 2025paperarXiv:2410.08299
1
citations
Provable unlearning in topic modeling and downstream tasks
Stanley Wei, Sadhika Malladi, Sanjeev Arora et al.
ICLR 2025arXiv:2411.12600
2
citations
Sherkala-Chat: Building a State-of-the-Art LLM for Kazakh in a Moderately Resourced Setting
Fajri Koto, Rituraj Joshi, Nurdaulet Mukhituly et al.
COLM 2025paper
5
citations
The Hyperfitting Phenomenon: Sharpening and Stabilizing LLMs for Open-Ended Text Generation
Fredrik Carlsson, Fangyu Liu, Daniel Ward et al.
ICLR 2025arXiv:2412.04318
4
citations
Toward Understanding In-context vs. In-weight Learning
Bryan Chan, Xinyi Chen, Andras Gyorgy et al.
ICLR 2025arXiv:2410.23042
15
citations
Bayesian Power Steering: An Effective Approach for Domain Adaptation of Diffusion Models
Ding Huang, Ting Li, Jian Huang
ICML 2024arXiv:2406.03683
1
citations
Erasing the Bias: Fine-Tuning Foundation Models for Semi-Supervised Learning
Kai Gan, Tong Wei
ICML 2024arXiv:2405.11756
22
citations
Fine-tuning Reinforcement Learning Models is Secretly a Forgetting Mitigation Problem
Maciej Wołczyk, Bartłomiej Cupiał, Mateusz Ostaszewski et al.
ICML 2024spotlightarXiv:2402.02868
26
citations
Learning to Obstruct Few-Shot Image Classification over Restricted Classes
Amber Yijia Zheng, Chiao-An Yang, Raymond Yeh
ECCV 2024arXiv:2409.19210
4
citations
Two-stage LLM Fine-tuning with Less Specialization and More Generalization
Yihan Wang, Si Si, Daliang Li et al.
ICLR 2024arXiv:2211.00635
43
citations