AI RESEARCH
STaR-Quant: State-Time Consistent Post-Training Quantization for Diffusion Large Language Models
arXiv CS.LG
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ArXi:2606.04945v1 Announce Type: new Diffusion large language models (DLLMs) have recently emerged as a promising alternative to autoregressive LLMs by generating text through iterative masked denoising with bidirectional context. However, their large model sizes and iterative denoising process