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Forget real-world video datasets: training VLMs on just 7.7K synthetic videos with temporal primitives beats 165K real-world examples, unlocking surprisingly effective transfer learning for video reasoning.
LLMs can escape the trap of converging on popular but incorrect answers in unsupervised RLVR by temporarily "unlearning" and exploring diverse response options.
Smart glasses powered by web-native AI agents can now outperform commercial solutions in assistive tasks, offering a practical path to always-on, context-aware help for users navigating daily life.
Autonomous driving gets a human-like reasoning boost: MindDriver uses progressive multimodal reasoning to bridge the gap between semantic understanding and physical trajectory planning.
