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Robots can achieve remarkable generalization in unpredictable environments using a lightweight feedback mechanism, even with minimal training data.
ConvergeFlow guarantees convergence to valid token embeddings, eliminating the need for cross-entropy supervision in flow-based language models.
Blurry structures and temporal flicker in driving scene rendering can be effectively mitigated using a unified framework that leverages spatial and temporal cues across datasets.
