A boundary-protection PTQ strategy for Wan2.1-T2V-14B matches BF16 VBench performance by retaining boundary blocks in higher precision and quantizing the rest to W8A8 HiF8.
Ascend HiFloat8 format for deep learning,
4 Pith papers cite this work. Polarity classification is still indexing.
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UNVERDICTED 4representative citing papers
Error analysis and cost estimator for recasting floating-point matrix multiplication as accumulated integer products on mixed-precision hardware.
GoldenFloat introduces a phi-derived rule for setting exponent and fraction widths across floating-point formats from 4 to 1024 bits, backed by open RTL generator, Lucas-exact accumulator, and FPGA implementation.
OSP-Next reports 83.73% VBench score and up to 2.27x speedup via hybrid sparse attention, SSP parallelism, HiF8 quantization, and Mix-GRPO on diffusion transformers.
citing papers explorer
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Boundary-Protection W8A8 HiFloat8 Quantization for Large-Scale Text-to-Video Diffusion Transformers
A boundary-protection PTQ strategy for Wan2.1-T2V-14B matches BF16 VBench performance by retaining boundary blocks in higher precision and quantizing the rest to W8A8 HiF8.
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Analysis of Floating-Point Matrix Multiplication Computed via Integer Arithmetic
Error analysis and cost estimator for recasting floating-point matrix multiplication as accumulated integer products on mixed-precision hardware.
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GoldenFloat: A Phi-Derived Static-Split Floating-Point Family from GF4 to GF1024 with a Lucas-Exact Integer Identity
GoldenFloat introduces a phi-derived rule for setting exponent and fraction widths across floating-point formats from 4 to 1024 bits, backed by open RTL generator, Lucas-exact accumulator, and FPGA implementation.
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OSP-Next: Efficient High-Quality Video Generation with Sparse Sequence Parallelism, HiF8 Quantization, and Reinforcement Learning
OSP-Next reports 83.73% VBench score and up to 2.27x speedup via hybrid sparse attention, SSP parallelism, HiF8 quantization, and Mix-GRPO on diffusion transformers.