Assistant Professor, University of Texas at Austin
2 papers at NeurIPS 2025
We propose a method to speedup video diffusion generation through efficient attention.
We present a model-aware approach that leverages the model’s own signals to dynamically choose training data, markedly boosting both training and data efficiency in RL fine-tuning.
