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The University of Hong Kong
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EntroRouter achieves near-optimal expert accuracy while slashing computational costs by nearly half, challenging the status quo of model routing efficiency.
Training with large block sizes cripples reasoning performance, but a novel curriculum approach unlocks strong reasoning capabilities in diffusion models.
A self-evolving training framework that tailors spatial reasoning tasks to a model's current capabilities can dramatically enhance performance while minimizing data inefficiency.
