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End-to-end driving gets a reliability boost: UniUncer's unified uncertainty framework slashes trajectory error by 7% and improves driving performance by 10.8% in challenging scenarios.
Achieve state-of-the-art ECG analysis by disentangling modality-specific biases and capturing spatial-temporal dependencies, outperforming existing multimodal approaches.
Forget full-cache rollouts: this parameter-efficient fine-tuning method lets large reasoning models maintain accuracy while slashing memory usage during RL training.
Forget scaling laws: teaching LLMs to learn from feedback lets smaller models rival giants and generalize to new tasks.
