3 citations · 6 across the 6 of their papers we have counts for
11 papers
Data-regularized Reinforcement Learning for Diffusion Models at Scale
Haotian Ye, Kaiwen Zheng, Jiashu Xu +15
Aligning generative diffusion models with human preferences via reinforcement learning (RL) is critical yet challenging. Most existing algorithms are often vulnerable to reward hac…
Scalable Policy Evaluation with Video World Models
Wei-Cheng Tseng, Jinwei Gu, Qinsheng Zhang +4
Training generalist policies for robotic manipulation has shown great promise, as they enable language-conditioned, multi-task behaviors across diverse scenarios. However, evaluati…
World Simulation with Video Foundation Models for Physical AI
NVIDIA, :, Arslan Ali +87
We introduce [Cosmos-Predict2.5], the latest generation of the Cosmos World Foundation Models for Physical AI. Built on a flow-based architecture, [Cosmos-Predict2.5] unifies Text2…
DiffusionNFT: Online Diffusion Reinforcement with Forward Process
Kaiwen Zheng, Huayu Chen, Haotian Ye +7
Online reinforcement learning (RL) has been central to post-training language models, but its extension to diffusion models remains challenging due to intractable likelihoods. Rece…
NFT: Bridging Supervised Learning and Reinforcement Learning in Math Reasoning
Huayu Chen, Kaiwen Zheng, Qinsheng Zhang +8
Reinforcement Learning (RL) has played a central role in the recent surge of LLMs' math abilities by enabling self-improvement through binary verifier signals. In contrast, Supervi…
Generalized Neighborhood Attention: Multi-dimensional Sparse Attention at the Speed of Light
Ali Hassani, Fengzhe Zhou, Aditya Kane +13
Many sparse attention mechanisms such as Neighborhood Attention have typically failed to consistently deliver speedup over the self attention baseline. This is largely due to the l…