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stat.ML2026
Why Self-Training Helps and Hurts: Denoising vs. Signal Forgetting
Mingqi Wu, Archer Y. Yang, Qiang Sun
Iterative self-training (self-distillation) repeatedly refits a model on pseudo-labels generated by its own predictions. We study this procedure in overparameterized linear regress…
stat.ML2026
Training-Free Self-Correction for Multimodal Masked Diffusion Models
Yidong Ouyang, Panwen Hu, Zhengyan Wan +7
Masked diffusion models have emerged as a powerful framework for text and multimodal generation. However, their sampling procedure updates multiple tokens simultaneously and treats…
stat.ML2025
PCA++: How Uniformity Induces Robustness to Background Noise in Contrastive Learning
Mingqi Wu, Qiang Sun, Yi Yang
High-dimensional data often contain low-dimensional signals obscured by structured background noise, which limits the effectiveness of standard PCA. Motivated by contrastive learni…