publications

2026

1. 

   When Errors Can Be Beneficial: A Categorization of Imperfect Rewards for Policy Gradient

   Shuning Shang^*, Hubert Strauss^*, Stanley Wei, Sanjeev Arora, and Noam Razin

   arXiv preprint arXiv:2604.25872, 2026

   Bib PDF Code

   @article{shang2026when,
     title = {When Errors Can Be Beneficial: A Categorization of Imperfect Rewards for Policy Gradient},
     author = {Shang, Shuning and Strauss, Hubert and Wei, Stanley and Arora, Sanjeev and Razin, Noam},
     journal = {arXiv preprint arXiv:2604.25872},
     year = {2026}
   }

2025

1. 

   Hardware-Efficient Attention for Fast Decoding

   Ted Zadouri, Hubert Strauss, and Tri Dao

   In Conference on Language Modeling (COLM 2025), 2025

   Bib PDF Code

   @inproceedings{zadouri2025hardwareefficientattentionfastdecoding,
     title = {Hardware-Efficient Attention for Fast Decoding},
     author = {Zadouri, Ted and Strauss, Hubert and Dao, Tri},
     booktitle = {Conference on Language Modeling},
     year = {2025},
   }

2. 

   What Makes a Reward Model a Good Teacher? An Optimization Perspective

   Noam Razin, Zixuan Wang, Hubert Strauss, Stanley Wei, Jason D Lee, and Sanjeev Arora

   In Advances in Neural Information Processing Systems (NeurIPS 2025), 2025

   Bib PDF Code Poster

   @inproceedings{razin2025what,
     title = {What Makes a Reward Model a Good Teacher? An Optimization Perspective},
     author = {Razin, Noam and Wang, Zixuan and Strauss, Hubert and Wei, Stanley and Lee, Jason D and Arora, Sanjeev},
     booktitle = {Advances in Neural Information Processing Systems},
     year = {2025},
   }

2024

1. 

   FutureFill: Fast Generation from Convolutional Sequence Models

   Naman Agarwal, Xinyi Chen, Evan Dogariu, Devan Shah, Hubert Strauss, Vlad Feinberg, Daniel Suo, Peter Bartlett, and Elad Hazan

   In International Conference on Learning Representations (ICLR 2026), 2024

   Bib PDF

   @inproceedings{agarwal2025futurefillfastgenerationconvolutional,
     title = {FutureFill: Fast Generation from Convolutional Sequence Models},
     author = {Agarwal, Naman and Chen, Xinyi and Dogariu, Evan and Shah, Devan and Strauss, Hubert and Feinberg, Vlad and Suo, Daniel and Bartlett, Peter and Hazan, Elad},
     booktitle = {International Conference on Learning Representations},
     year = {2024},
   }