🌍 TL;DR: A training-free way to re-explore a recorded video from new camera angles just dropped. It handles viewpoint changes, hole-filling, and recovering earlier appearances entirely through a frozen model's own attention. Title: World in World: Explore the World with World Models URL: Points 🎥 Four evidence sources (source video, target-view scene, rendered geometry, retrieved history) get converted into clean K/V fed straight into the frozen model 🧭 CGAR routes queries toward reliable source-video tokens using persistent point correspondence and camera geometry 🎚 EWA independently tunes each auxiliary channel's contribution using existing attention outputs, with zero extra network evaluations 🏆 Top VBench score of 85.192 and lowest rotation error (2.8326°) against 6 baselines including ReCamMaster 🔧 Same framework also powers bullet-time rendering, video stabilization, editing, and motion transfer Getting this much versatility with zero retraining feels like a win for evidence engineering over model adaptation. #WorldModels# #VideoGeneration#