zero-shot-generalization

EgoPhys introduces a framework to construct deformable physical digital twins from egocentric RGB video using generalizable priors and a compact codebook, enabling zero-shot generalization to unseen objects without per-spring optimization. The system is demonstrated on a real robot, showing that egocentric human play video can serve as internal world representation for deformable-object planning.

Introduces PCSP, a single RL policy conditioned on frozen LLM embeddings of persona descriptions, enabling scalable, real-time persona-traceable NPC control in life simulation games. Experiments show zero-shot persona identification and behavioral alignment, with faster inference than LLM baselines.