KlingAI's ALLOT Allocates Block-Sparse Attention by Output Tests, Training-Free
KlingTeam · hf · 2026-10-22
ALLOT is a training-free method that allocates block-sparse attention densities across layer-step pairs in video diffusion transformers. Key insight: sparsity sensitivity differs substantially across layers and denoising steps yet is input-stable. ALLOT treats each layer-step's latency budget as an allocation unit chosen by output tests, maximizing fidelity under a latency budget.
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