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

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2025

Elucidated Rolling Diffusion Models for Probabilistic Weather Forecasting
Salva Rühling Cachay, Miika Aittala, Karsten Kreis, Noah Brenowitz, Arash Vahdat, Morteza Mardani, Rose Yu
Align Your Flow: Scaling Continuous-Time Flow Map Distillation
Amirmojtaba Sabour, Sanja Fidler, Karsten Kreis
ThinkAct: Vision-Language-Action Reasoning via Reinforced Visual Latent Planning
Chi-Pin Huang, Yueh-Hua Wu, Min-Hung Chen, Frank Wang, Fred Yang
Seeing What Matters: Generalizable AI-generated Video Detection with Forensic-Oriented Augmentation
Riccardo Corvi, Davide Cozzolino, Ekta Prashnani, Shalini De Mello, Koki Nagano, Luisa Verdoliva
Alpamayo-R1: Bridging Reasoning and Action Prediction for Generalizable Autonomous Driving in the Long Tail
Marco Pavone, Many other contributors found on Page 33
VoiceNoNG: Robust High-Quality Speech Editing Model without Hallucinations
Sung-Feng Huang, Heng-Cheng Kuo, Zhehuai Chen, Xuesong Yang, Pin-Jui Ku, Ante Jukić, Huck Yang, Yu Tsao, Frank Wang, Hung-yi Lee, Szu-Wei Fu
Assessing Learned Models for Phase-only Hologram Compression
Zicong Peng, Yicheng Zhan, Josef Spjut, Kaan Akşit
GAIA: Generative Animatable Interactive Avatars with Expression-conditioned Gaussians
Zhengming Yu, Tianye Li, Jingxiang Sun, Omer Shapira, Seonwook Park, Michael Stengel, Matthew Chan, Xin Li, Wenping Wang, Koki Nagano, Shalini De Mello
Fly, Fail, Fix: Iterative Game Repair with Reinforcement Learning and Large Multimodal Models
Alex Zook, Josef Spjut, Jonathan Tremblay
Identity-Motion Trade-offs in Text-to-Video Generation
Yuval Atzmon, Rinon Gal, Yoad Tewel, Yoni Kasten, Gal Chechik
FourCastNet 3: A geometric approach to probabilistic machine-learning weather forecasting at scale
Boris Bonev, Thorsten Kurth, Ankur Mahesh, Mauro Bisson, Jean Kossaifi, Karthik Kashinath, Anima Anandkumar, William D. Collins, Mike Pritchard, Alex Keller
GenMol: A Drug Discovery Generalist with Discrete Diffusion
Seul Lee, Karsten Kreis, Srimukh Prasad Veccham, Meng Liu, Danny Reidenbach, Yuxing Peng, Saee Paliwal, Weili Nie, Arash Vahdat
Efficient Molecular Conformer Generation with SO(3)-Averaged Flow Matching and Reflow
Zhonglin Cao, Mario Geiger, Allan Dos Santos Costa, Danny Reidenbach, Karsten Kreis, Tomas Geffner, Franco Pellegrini, Guoqing Zhou, Emine Kucukbenli
Score-based Diffusion Models in Function Space
Jae Hyun Lim, Nikola Kovachki, Ricardo Baptista, Christopher Beckham, Kamyar Azizzadenesheli, Jean Kossaifi, Vikram Voleti, Jiaming Song, Karsten Kreis, Jan Kautz, Christopher Pal, Arash Vahdat, Anima Anandkumar
Make It Count: Text-to-Image Generation with an Accurate Number of Objects
Lital Binyamin, Yoad Tewel, Eran Hirsch, Royi Rassin, Gal Chechik
Coherent 3D Portrait Video Reconstruction via Triplane Fusion
Shengze Wang, Xueting Li, Chao Liu, Matthew Chan, Michael Stengel, Henry Fuchs, Shalini De Mello, Koki Nagano
SimAvatar: Simulation-Ready Clothed Gaussian Avatars from Text
Xueting Li, Ye Yuan, Shalini De Mello, Gilles Daviet, Jonathan Leaf, Miles Macklin, Jan Kautz, Umar Iqbal
A Generative AI Game Jam Case Study from October 2024
Josef Spjut
Beyond the Buzz: A Pragmatic Take on Inference Disaggregation
Tiyasa Mitra, Ritika Borkar, Nidhi Bhatia, Ramon Matas, Shivam Raj, Dheevatsa Mudigere, Ritchie Zhao, Maximilian Golub, Arpan Dutta, Sailaja Madduri, Dharmesh Jani, Brian Pharris, Bita Darvish Rouhani
Inference-Time Policy Steering through Human Interactions
Yanwei Wang, Lirui Wang, Yilun Du, Balakumar Sundaralingam, Xuning Yang, Yu-Wei Chao, Claudia Pérez D’Arpino , Dieter Fox, Julie Shah
Score Distillation Sampling for Audio: Source Separation, Synthesis, and Beyond
Jessie Richter-Powell, Antonio Torralba, Jonathan Lorraine
Fugatto 1 - Foundational Generative Audio Transformer Opus 1
Rafael Valle, Rohan Badlani, Zhifeng Kong, Sang-gil Lee, Arushi Goel, Sungwon Kim, Joao Felipe Santos, Shuqi Dai, Siddharth Gururani, Aya AIJa'fari, Alex Liu, Kevin Shih, Wei Ping, Huck Yang, Bryan Catanzaro
UniWav: Towards Unified Pre-training for Speech Representation Learning and Generation
Alexander H. Liu, Sang-gil Lee, Huck Yang, Yuan Gong, Frank Wang, James R. Glas, Rafael Valle
Lightning-Fast Image Inversion and Editing for Text-to-Image Diffusion Models,
Dvir Samuel, Barak Meiri, Haggai Maron, Yoad Tewel, Nir Darshan, Shai Avidan, Gal Chechik, Rami Ben-Ari
Cosmos Transfer 1: World-to-World Transfer with Adaptive Multi-Control for Physical AI
Ming-Yu Liu
Cosmos-Reason 1: From Physical AI Common Sense to Embodied Decisions
Tsung-Yi Lin, Ming-Yu Liu
NVIDIA Isaac GR00T N1: An Open Foundation Model for Humanoid Robots
Yuke Zhu, Linxi "Jim" Fan, NVIDIA GEAR Team
LLaMA-Mesh: Unifying 3D Mesh Generation with Language Models
Zhengyi Wang, Jonathan Lorraine, Yikai Wang, Hang Su, Jun Zhu, Sanja Fidler, Xiaohui Zeng
Multi-student Diffusion Distillation for Better One-step Generators
Yanke Song, Jonathan Lorraine, Weili Nie, Karsten Kreis, James Lucas
CorrFill: Enhancing Faithfulness in Reference-based Inpainting with Correspondence Guidance in Diffusion Models
Kuan-Hung Liu, Cheng-Kun Yang, Min-Hung Chen, Yu-Lun Liu, Yen-Yu Lin
Energy-Based Diffusion Language Models for Text Generation
Minkai Xu, Tomas Geffner, Karsten Kreis, Weili Nie, Yilun Xu, Jure Leskovec, Stefano Ermon, Arash Vahdat
Truncated Consistency Models
Sangyun Lee, Yilun Xu, Tomas Geffner, Giulia Fanti, Karsten Kreis, Arash Vahdat, Weili Nie