DashAttention：可微分且可适应的稀疏层级注意力机制
本文提出 DashAttention，一种可微分且可适应的稀疏层级注意力机制。该方法通过层级稀疏化策略显著降低计算复杂度，同时保持模型表达能力。实验表明，DashAttention 在长序列任务中能有效平衡效率与性能，为 Transformer 模型的注意力机制优化提供了新思路。
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