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Express achieves a groundbreaking reduction in approximation error and memory usage for causal attention, outperforming existing methods and enabling more efficient long-context language modeling.
Get faster convergence in entropy-regularized learning tasks: Kernel Thinning slashes the computational cost of Mean Field Langevin Dynamics while preserving its theoretical guarantees.
