3 accepted papers
Diffusion transformer models deliver state-of-the-art image synthesis quality but suffer from prohibitively slow iterative sampling. Although reducing sampling steps accelerates inference, aggressive step schedules often distort intermediate features and degrade sample fidelity. We present GeoRK2, a
Information-based data selection for instruction tuning is compelling: maximizing the log-determinant of the Fisher information yields a monotone submodular objective, enabling greedy algorithms to achieve a $(1-1/e)$ approximation under a cardinality budget. In practice, however, we identify allevi…
In real-life conversations, the content is diverse, and there exist one-to-many problems that require diverse generation. Previous studies attempted to introduce discrete or Gaussian-based latent variables to address the one-to-many problem, but the diversity is limited. Recently, diffusion models h…