Publications

Our publications provide insight into some of our leading-edge research.

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2026

GalaxyDiT: Efficient Video Generation with Guidance Alignment and Adaptive Proxy in Diffusion Transformers
Zoey Song, Steve Dai, Ben Keller, Brucek Khailany
ScheduleStream: Temporal Planning with Samplers for GPU-Accelerated Multi-Arm Task and Motion Planning & Scheduling
Caelan Garrett, Fabio Ramos
Test-Time Alignment for Large Language Models via Textual Model Predictive Control
Kuang-Da Wang, Teng-Ruei Chen, Yu Heng Hung, Guo-Xun Ko, Shuoyang Ding, Frank Wang, Huck Yang, Wen-Chih Peng, Ping-Chun Hsieh
3D-GENERALIST: Vision-Language-Action Models for Crafting 3D Worlds
Fan-Yun Sun, Shengguang Wu, Christian Jacobsen, Thomas Yim, Haoming Zou, Alex Zook, Shangru Li, Yu-Hsin Chou, Ethem Can, Xunlei Wu, Clemens Eppner, Valts Blukis, Jonathan Tremblay, Jiajun Wu, Stan Birchfield, Nick Haber
SPEED-Bench: A Unified and Diverse Benchmark for Speculative Decoding
Talor Abramovich, Maor Ashkenazi, Carl Putterman, Benjamin Chislett, Tiyasa Mitra, Bita Darvish Rouhani, Ran Zilberstein, Yonatan Geifman
Alpha-Vision: A Real-Time Always-on Vision Processor with 787µs Face Detection Latency in <5mW
Ben Keller, Rangharajan Venkatesan, Steve Dai, Jason Clemons, Matt Fojtik, Muya Chang, Thierry Tambe, Nathaniel Pinckney, Stephen Tell, Qijing Jenny Huang, Shalini De Mello, Brucek Khailany
Learning Accurate Storm-Scale Evolution from Observations
Jaideep Pathak, Mohammad Shoaib Abbas, Peter Harrington, Zeyuan Hu, Noah Brenowitz, Suman Ravuri, Alberto Carpentieri, Jussi Leinonen, Corey Adams, Oliver Hennigh, Nicholas Geneva, Dale Durran, Mike Pritchard
HealDA: Highlighting the importance of initial errors in end-to-end AI weather forecasts
Aayush Gupta, Akshay Subramaniam, Michael S. Pritchard, Karthik Kashinath, Sergey Frolov, Kelsey Lieberman, Christopher Miller, Nicholas Silverman, Noah D. Brenowitz
Demystifying Data-Driven Probabilistic Medium-Range Weather Forecasting
Jean Kossaifi, Nikola Kovachki, Morteza Mardani, Daniel Leibovici, Suman Ravuri, Ira Shokar, Edoardo Calvello, Mohammad Shoaib Abbas, Peter Harrington, Ashay Subramaniam, Noah Brenowitz, Boris Bonev, Wonmin Byeon, Karsten Kreis, Dale Durran, Arash Vahdat, Mike Pritchard, Jan Kautz

2020

NVCell: Generate Standard Cell Layout in Advanced Technology Nodes with Reinforcement Learning
Mark Haoxing Ren, Matt Fojtik, Brucek Khailany
Set2Graph: Learning Graphs From Sets
Hadar Serviansky, Nimrod Segol, Jonathan Shlomi, Kyle Cranmer, Eilam Gross, Haggai Maron, Yaron Lipman
Online Adaptation for Consistent Mesh Reconstruction in the Wild
Xueting Li, Sifei Liu, Shalini De Mello, Kihwan Kim, Xiaolong Wang, Ming-Hsuan Yang, Jan Kautz
Self-Learning Transformations for Improving Gaze and Head Redirection
Yufeng Zheng, Seonwook Park, Xucong Zhang, Shalini De Mello, Otmar Hilliges
A Causal View of Compositional Zero-Shot Recognition
Yuval Atzmon, Felix Kreuk, Uri Shalit, Gal Chechik
Bongard-LOGO: A New Benchmark for Human-Level Concept Learning and Reasoning
Weili Nie, Zhiding Yu, Lei Mao, Ankit B. Patel, Yuke Zhu, Anima Anandkumar
Neural Networks with Recurrent Generative Feedback
Yujia Huang, James Gornet, Sihui Dai, Zhiding Yu, Tan Nguyen, Doris Y. Tsao, Anima Anandkumar
Learning Deformable Tetrahedral Meshes for 3D Reconstruction
Jun Gao, Wenzheng Chen, Tommy Xiang, Clement Fuji Tsang, Alec Jacobson, Morgan McGuire
Convolutional Tensor-Train LSTM for Spatio-Temporal Learning
Jiahao Su, Wonmin Byeon, Jean Kossaifi, Furong Huang, Jan Kautz, Anima Anandkumar
Accelerating Reinforcement Learning through GPU Atari Emulation
Iuri Frosio, Steven Dalton
Training Generative Adversarial Networks with Limited Data
Tero Karras, Miika Aittala, Janne Hellsten, Samuli Laine, Jaakko Lehtinen, Timo Aila
Variational Amodal Object Completion
Huan Ling, David Acuna, Karsten Kreis, Seung Wook Kim, Sanja Fidler
Neural FFTs for Universal Texture Image Synthesis
Morteza Mardani, Guilin Liu, Aysegul Dundar, Shiqiu Liu, Andrew Tao, Bryan Catanzaro
Neural Control Variates
Thomas Müller, Fabrice Rousselle, Alex Keller, Jan Novák
ZEST: Zero-shot Learning from Text Descriptions using Textual Similarity and Visual Summarization
Tzuf Paz-Argaman, Yuval Atzmon, Gal Chechik, Reut Tsarfaty
Generating and Characterizing Scenarios for Safety Testing of Autonomous Vehicles
Zahra Ghodsi, Siva Hari, Iuri Frosio, Timothy Tsai, Alejandro Troccoli, Steve Keckler, Siddharth Garg, Anima Anandkumar
Generating and Characterizing Scenarios for Safety Testing of Autonomous Vehicles
Zahra Ghodsi, Siva Hari, Iuri Frosio, Timothy Tsai, Alejandro Troccoli, Steve Keckler, Siddharth Garg, Anima Anandkumar
Modular Primitives for High-Performance Differentiable Rendering
Samuli Laine, Janne Hellsten, Tero Karras, Yeongho Seol, Jaakko Lehtinen, Timo Aila
Learning Object Permanence from Video
Aviv Shamsian, Ofri Kleinfeld, Amir Globerson, Gal Chechik
A Programmable Approach to Neural Network Compression
Vinu Joseph, Ganesh L. Gopalakrishnan, Saurav Muralidharan, Michael Garland, Animesh Garg
Accelerating Chip Design with Machine Learning
Brucek Khailany, Mark Haoxing Ren, Steve Dai, Saad Godil, Ben Keller, Robert Kirby, Alicia Klinefelter, Rangharajan Venkatesan, Yanqing Zhang, Bryan Catanzaro, William Dally
HarDNN: Fine-Grained Vulnerability Evaluation and Protection for Convolutional Neural Networks
Abdulrahman Mahmoud, Siva Hari, Christopher W. Fletcher, Sarita V. Adve, Charbel Sakr, Naresh Shanbhag, Pavlo Molchanov, Michael B. Sullivan, Timothy Tsai, Steve Keckler
UNAS: Differentiable Architecture Search Meets Reinforcement Learning
Arash Vahdat, Arun Mallya, Ming-Yu Liu, Jan Kautz