world-compass-rl-world-models

Improve long-horizon world model fidelity using RL with clip-level rollouts and complementary reward functions for action accuracy and visual quality. Breaks computational constraints by evaluating candidate clips incrementally rather than full sequences, enabling efficient multi-objective optimization.

Independent GitHub snapshot · Automated classification · Original documentation governs