NLD-Uni unifies visual understanding and generation in a diffusion LLM
Cross-paradigm distillation and progressive token corruption are used instead of conventional masked diffusion.
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Cross-paradigm distillation and progressive token corruption are used instead of conventional masked diffusion.
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SpecFold reuses multi-branch computation to speed diffusion-LLM speculative decoding by up to 1.99×.
SoloQ quantizes diffusion language models to 4-bit without calibration, cutting memory up to 2.61x with NVFP4.
Flash-dLLM speeds diffusion LLM inference with I/O-aware KV caching and parallel draft-and-verify decoding.
Flash-dLLM accelerates diffusion LLM inference with I/O-aware KV caching, up to 11 times faster than Elastic-Cache.
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