Auguste Hadamard
PulseAugur coverage of Auguste Hadamard — every cluster mentioning Auguste Hadamard across labs, papers, and developer communities, ranked by signal.
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Uniform INT4 quantization outperforms NVFP4 on real gradient tensors
A study comparing quantization palettes for gradient tensors found that a uniform INT4 palette outperformed NVIDIA's NVFP4 palette on real-world training data. The research suggests that the random Hadamard rotation, of…
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RoPE-Aligned Rotations Fail to Improve 4-Bit Quantization Accuracy
A new research paper explores the effectiveness of RoPE-aligned Q/K rotations for dynamic 4-bit quantization in language models. The study found that while pairwise rotations can commute with RoPE, they do not improve a…
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New research predicts neural network training efficiency with random reparameterizations
A new research paper introduces Random Mapping Networks (RaMaN), a method designed to predict when random low-dimensional reparameterizations can effectively train neural networks. The paper proposes an orientation-reso…
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New technique improves Transformer KV cache compression
Researchers have developed Codec-Gauge, a post-training layer designed to improve the compression of Key-Value (KV) caches in long-context Transformer models. This method learns orthogonal channel transforms that optimi…
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New KReTTaH framework offers data-free imputation via tensor trains
A new framework called KReTTaH has been introduced for multi-way data imputation, utilizing kernel regression with tensor trains and Hadamard overparameterization. This method is designed to be training-data-free, inter…