Search papers, labs, and topics across Lattice.
STRATA achieves 50x better energy efficiency than conventional storm-resolving models while delivering realistic global weather simulations at kilometer-scale resolution.
Policies trained in SimFoundry's automated environments achieve up to 40% higher success rates in real-world tasks by leveraging affordance-preserving scene variations.
Physically aligned video models can boost robotic manipulation success rates by over 50% compared to traditional methods.
Post-training on synthesized safety-critical scenarios can dramatically enhance the reliability of autonomous driving systems, reducing failures in rare but critical events.
A single generalist model outperforms specialized systems, achieving over 35% improvement in real-world robotic task success.
VLMs trained on the new 4DP-QA dataset show marked improvements in understanding complex 4D scenes, revealing the critical role of disentangling motion dynamics.
Retaining the right evidence before a query can boost long-horizon agent performance by over 70% in F1 score, transforming how we think about memory management in AI.
Cosmos 3 sets a new benchmark for omnimodal models, outperforming existing state-of-the-art in both Text-to-Image and Image-to-Video tasks.
Steering imaginations in video world models can reveal critical failure points in robotic actions that traditional methods might overlook.
Achieving a 40x speedup in training for deformable simulations could revolutionize real-time applications in robotics and animation.
A generative model of human physiology not only beats existing clinical risk scores at predicting disease, but also accurately simulates the effects of clinical interventions, paving the way for personalized medicine.
VLN agents can navigate more accurately in zero-shot settings by "looking forward, now, and backward," mimicking human navigational strategies.
Existing robotic methods falter in tackling fundamental physical reasoning challenges, as evidenced by KinDER's rigorous benchmark evaluation.
Sonata outperforms traditional models in clinical kinematic assessments, achieving better fall-risk predictions with a fraction of the parameters.
Fusing MPC with RL yields safer and more efficient autonomous driving at intersections, outperforming both standalone MPC and end-to-end RL, and surprisingly generalizing better to new scenarios.
RoboLab exposes critical performance gaps in leading robotic models, revealing that high-fidelity simulations can better assess generalization than traditional benchmarks.
Finally, a video generation model lets you puppeteer objects and their reactions independently, all while freely moving the camera.
Training generalist robots just got a whole lot easier: RoboCasa365 offers a massive, diverse, and reproducible benchmark for household mobile manipulation.
Forget synthetic data that looks like it came from a PS2 game: NVIDIA's new Cosmos-Predict2.5 generates high-fidelity videos for training embodied AI, opening the door to more realistic and reliable simulations.
