4 papers
Training-Free Adaptation of Diffusion Models via Doob's -Transform
Qijie Zhu, Zeqi Ye, Han Liu +2
Adaptation methods have been a workhorse for unlocking the transformative power of pre-trained diffusion models in diverse applications. Existing approaches often abstract adaptati…
Parameter-Efficient Subspace Optimization for LLM Fine-Tuning
Yuchen Lou, Zeqi Ye, Minshuo Chen
This paper develops a new perspective on parameter-efficient fine-tuning (PEFT) for LLMs, inspired by classical subspace minimization. We introduce a unifying framework, Parameter-…
Provable Separations between Memorization and Generalization in Diffusion Models
Zeqi Ye, Qijie Zhu, Molei Tao +1
Diffusion models have achieved remarkable success across diverse domains, but they remain vulnerable to memorization -- reproducing training data rather than generating novel outpu…
Diffusion Transformers for Imputation: Statistical Efficiency and Uncertainty Quantification
Zeqi Ye, Minshuo Chen
Imputation methods play a critical role in enhancing the quality of practical time-series data, which often suffer from pervasive missing values. Recently, diffusion-based generati…