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German Cancer Research Center
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Non-contrastive pretraining can yield dense semantic features that outperform traditional contrastive methods in vision-language tasks.
Model-based reinforcement learning slashes CNOT gate count in quantum circuits by up to 32%, outperforming heuristic and model-free RL methods.
