Tianchang Shen

A real-time generative world model can synthesize complex driving scenarios that traditional simulators struggle to capture, enabling safer and more effective evaluation of autonomous vehicle policies.

Forget fixed agent slots and quadratic attention: Gamma-World uses simplex embeddings and sparse hubs to generate interactive multi-agent environments with better fidelity and control, even generalizing from 2 to 4 players without retraining.

Forget generating static 3D scenes – Lyra 2.0 lets you create entire explorable 3D worlds by cleverly routing information from past frames and training the model to correct its own mistakes.

Finally, a video generation model lets you puppeteer objects and their reactions independently, all while freely moving the camera.

Achieve state-of-the-art depth completion by adapting 3D foundation models at test time with minimal parameter updates, outperforming task-specific encoders that often overfit.