AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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We introduce LLaDA-Image, a unified framework that pairs a 6B Diffusion Transformer (DiT) trained from scratch with a frozen vision-language understanding module built on the LLaDA2.0-Mini diffusion language model backbone. Instead of relying heavily on paired image-text data from the beginning, we first build a strong...
This work proposes Hyper-Spherical Quantization (HSQ), which decouples semantic content from feature magnitude via angular routing, preventing code assignment from being dominated by scale rather than meaning.
Chunked Muon (CMuon) is introduced, a simple yet highly effective strategy that partitions these matrices into independent sub-components prior to orthogonalization, effectively overcoming the late-stage convergence plateaus of vanilla Muon.
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