Zisheng Chen

BEE reduces inference latency and tool redundancy, achieving state-of-the-art performance in visual perception while maintaining competitive reasoning capabilities.

Continuous latent visual representations can drastically improve multimodal reasoning efficiency and performance, outpacing traditional discrete output methods.

IRR-Drive's innovative dual-modality approach enables autonomous vehicles to self-correct trajectories with unprecedented reliability in dynamic environments.

Forget monolithic action decoders: AtomicVLA's skill-guided mixture-of-experts unlocks significant gains in long-horizon robotic manipulation and continual learning.