ICLR 2025 "training efficiency" Papers
7 papers found
A CLIP-Powered Framework for Robust and Generalizable Data Selection
Suorong Yang, Peng Ye, Wanli Ouyang et al.
ICLR 2025posterarXiv:2410.11215
15
citations
Cut Your Losses in Large-Vocabulary Language Models
Erik Wijmans, Brody Huval, Alexander Hertzberg et al.
ICLR 2025posterarXiv:2411.09009
19
citations
Drop-Upcycling: Training Sparse Mixture of Experts with Partial Re-initialization
Taishi Nakamura, Takuya Akiba, Kazuki Fujii et al.
ICLR 2025posterarXiv:2502.19261
8
citations
Fewer May Be Better: Enhancing Offline Reinforcement Learning with Reduced Dataset
Yiqin Yang, Quanwei Wang, Chenghao Li et al.
ICLR 2025posterarXiv:2502.18955
Linear Combination of Saved Checkpoints Makes Consistency and Diffusion Models Better
Enshu Liu, Junyi Zhu, Zinan Lin et al.
ICLR 2025posterarXiv:2404.02241
6
citations
Rectified Diffusion: Straightness Is Not Your Need in Rectified Flow
Fu-Yun Wang, Ling Yang, Zhaoyang Huang et al.
ICLR 2025posterarXiv:2410.07303
47
citations
Representation Alignment for Generation: Training Diffusion Transformers Is Easier Than You Think
Sihyun Yu, Sangkyung Kwak, Huiwon Jang et al.
ICLR 2025posterarXiv:2410.06940
308
citations