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cs.CV2024
David and Goliath: Small One-step Model Beats Large Diffusion with Score Post-training
Weijian Luo, Colin Zhang, Debing Zhang +1
We propose Diff-Instruct* (DI*), a data-efficient post-training approach for one-step text-to-image generative models to improve its human preferences without requiring image data.…
cs.CL2024
Untie the Knots: An Efficient Data Augmentation Strategy for Long-Context Pre-Training in Language Models
Junfeng Tian, Da Zheng, Yang Cheng +3
Large language models (LLM) have prioritized expanding the context window from which models can incorporate more information. However, training models to handle long contexts prese…