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Yujun Lin

Yujun Lin

Senior Research Scientist

NVIDIA

Yujun Lin is a research scientist at NVIDIA. He finished his PhD at MIT, advised by Prof. Song Han. His research area is efficient deep learning, with a special focus on the co-design of algorithm, system and hardware for foundation models (diffusion models, LLMs, etc). His work has been featured as oral and spotlight presentations at conferences such as ICLR, NeurIPS, Micro, HPCA and MLSys.

Interests
  • Computer Vision
  • Machine Learning

Latest

  • Taming the Long-Tail: Efficient Reasoning RL Training with Adaptive Drafter
  • QeRL: Beyond Efficiency - Quantization-enhanced Reinforcement Learning for LLMs
  • DC-Gen: Post-Training Diffusion Acceleration with Deeply Compressed Latent Space
  • DC-VideoGen: Efficient Video Generation with Deep Compression Video Autoencoder
  • Radial Attention: $\mathcal{O}(n\log n)$ Sparse Attention with Energy Decay for Long Video Generation
  • Sparse VideoGen2: Accelerate Video Generation with Sparse Attention via Semantic-Aware Permutation
  • Sparse VideoGen: Accelerating Video Diffusion Transformers with Spatial-Temporal Sparsity
  • SANA 1.5: Efficient Scaling of Training-Time and Inference-Time Compute in Linear Diffusion Transformer
  • SVDQuant: Absorbing Outliers by Low-Rank Components for 4-Bit Diffusion Models
  • SANA: Efficient High-Resolution Image Synthesis with Linear Diffusion Transformer

© 2026 NVIDIA. This work is licensed under CC BY NC ND 4.0

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