3 papers
cs.LG2026
Diving into Kronecker Adapters: Component Design Matters
Jiayu Bai, Danchen Yu, Zhenyu Liao +4
Kronecker adapters have emerged as a promising approach for fine-tuning large-scale models, enabling high-rank updates through tunable component structures. However, existing work…
cs.LG2025
Latent Iterative Refinement Flow: A Geometric Constrained Approach for Few-Shot Generation
Songtao Li, Tianqi Hou, Zhenyu Liao +1
Diffusion and flow-matching models trained with limited data often tend to memorize the training data instead of generalization, leading to severely reduced diversity. In this pape…
stat.ML2025
On the Interpolation Error of Nonlinear Attention versus Linear Regression
Zhenyu Liao, Jiaqing Liu, TianQi Hou +2
Attention has become the core building block of modern machine learning (ML) by efficiently capturing the long-range dependencies among input tokens. Its inherently parallelizable…