Yann LeCun

Adaptive latent models can recalibrate in real-time, boosting planning success rates even in shifting environments.

Achieving robust zero-shot sim-to-real transfer for quadrotors, this work redefines the boundaries of long-horizon prediction in robotic control.

S-JEPA sets a new standard in speech representation learning by achieving top performance with fewer parameters and without the cumbersome offline re-clustering process.

Relying on causal relationships rather than strong inductive biases, TDV achieves state-of-the-art performance in visual representation learning, challenging the status quo of self-supervised methods.

WorldDP achieves superior performance in multi-stage robotic tasks by seamlessly integrating high-level planning with low-level execution, outperforming traditional methods.