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Low-bit quantization of linear layers is often dominated by a small number of outlier channels. Existing smoothing, rotation, and residual-based methods can mitigate this issue, but may shift the quantization bottleneck to weights or introduce costly online operations. To address these limitations, we propose PRQuant (...
The quadratic cost of attention is a major bottleneck in diffusion-based video generation models. MXFP4 attention provides a promising path toward efficient inference, but direct MXFP4 quantization often degrades generation quality due to two numerical issues: the clipping-underflow trade-off from power-of-two scaling...
Kaleido is presented, an algorithm hardware codesign that accelerates all operations in vDiTs by exploiting channel-wise spatiotemporal correlations in latent space and skips redundant computations by reusing partial results while preserving higher generative quality than prior methods.
BiSCo-LLM is presented, a codebook-free binary spherical coding framework for extreme low-bit LLM weight compression and its reported storage budget includes binary codes, neural decoders, protected-channel payloads, LoRA adapters, and metadata.
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