Search papers, labs, and topics across Lattice.
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.
