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cs.CL2025
ParoQuant: Pairwise Rotation Quantization for Efficient Reasoning LLM Inference
Yesheng Liang, Haisheng Chen, Zihan Zhang +2
Post-training quantization (PTQ) compresses the weights and activations of large language models (LLMs) into low-precision representations to reduce memory footprint and accelerate…
cs.CL2025
Fast-dLLM v2: Efficient Block-Diffusion LLM
Chengyue Wu, Hao Zhang, Shuchen Xue +7
Autoregressive (AR) large language models (LLMs) have achieved remarkable performance across a wide range of natural language tasks, yet their inherent sequential decoding limits i…
cs.CL2025
Fast-dLLM: Training-free Acceleration of Diffusion LLM by Enabling KV Cache and Parallel Decoding
Chengyue Wu, Hao Zhang, Shuchen Xue +6
Diffusion-based large language models (Diffusion LLMs) have shown promise for non-autoregressive text generation with parallel decoding capabilities. However, the practical inferen…