Zheng Li

LaST outperforms traditional models by harnessing the strengths of both large and small architectures, achieving unprecedented accuracy in zero-shot surgical phase recognition.

Dynamic integration of multimodal knowledge boosts the recognition of rare surgical actions, overcoming critical optimization conflicts in robot-assisted surgery.

Humanoid robots can now adapt to complex terrains in real-time by leveraging detailed plantar pressure feedback, achieving remarkable performance even on unseen surfaces.

Modular TTT reveals that the right combination of learning rate and weight decay can significantly boost performance, while deeper architectures may actually degrade results.