About Me
My name is David Li and I am a first-year PhD student at MBZUAI. My research interests are mainly in generative models, diffusion models, optimal transport, and related areas of machine learning. I am especially interested in making diffusion models faster through distillation approaches.
Highlights
ICML 2026
IDLM: Inverse-distilled Diffusion Language Models
Framework that distills diffusion language models into few-step generators while preserving entropy and generative perplexity.
ICML 2025Inverse Bridge Matching Distillation
A distillation objective for diffusion bridge models that accelerates image-to-image generation from hundreds of teacher steps to a few student steps.
ICLR 2026 (Oral)Universal Inverse Distillation for Matching Models with Real-Data Supervision
A universal inverse distillation framework that incorporates real data into matching-model distillation without GAN training.