1k citations · 2.3k across the 30 of their papers we have counts for
12 papers · 1 filter
Four Over Six: More Accurate NVFP4 Quantization with Adaptive Block Scaling
Jack Cook, Junxian Guo, Guangxuan Xiao +7
As large language models have grown larger, interest has grown in low-precision numerical formats such as NVFP4 as a way to improve speed and reduce memory usage. However, quantizi…
VLASH: Real-Time VLAs via Future-State-Aware Asynchronous Inference
Jiaming Tang, Yufei Sun, Yilong Zhao +7
Vision-Language-Action models (VLAs) are becoming increasingly capable across diverse robotic tasks. However, these models are typically deployed under synchronous inference, where…
Taming the Long-Tail: Efficient Reasoning RL Training with Adaptive Drafter
Qinghao Hu, Shang Yang, Junxian Guo +7
The emergence of Large Language Models (LLMs) with strong reasoning capabilities marks a significant milestone, unlocking new frontiers in complex problem-solving. However, trainin…
QeRL: Beyond Efficiency -- Quantization-enhanced Reinforcement Learning for LLMs
Wei Huang, Yi Ge, Shuai Yang +11
We propose QeRL, a Quantization-enhanced Reinforcement Learning framework for large language models (LLMs). While RL is essential for LLMs' reasoning capabilities, it is resource-i…
DC-VideoGen: Efficient Video Generation with Deep Compression Video Autoencoder
Junyu Chen, Wenkun He, Yuchao Gu +12
We introduce DC-VideoGen, a post-training acceleration framework for efficient video generation. DC-VideoGen can be applied to any pre-trained video diffusion model, improving effi…
LEGO: Spatial Accelerator Generation and Optimization for Tensor Applications
Yujun Lin, Zhekai Zhang, Song Han
Modern tensor applications, especially foundation models and generative AI applications require multiple input modalities (both vision and language), which increases the demand for…