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cs.LG2026
Cluster-Level Attention-Guided Parallel Decoding for Masked Diffusion Language Models
Heqiang Qi, Wei Huang, Mingyuan Bai +1
Masked diffusion language models (MDLMs) enable parallel decoding by predicting all masked positions at each denoising step, yet existing training-free samplers usually decide whic…
cs.CL2026
GradPruner: Gradient-Guided Layer Pruning Enabling Efficient Fine-Tuning and Inference for LLMs
Wei Huang, Anda Cheng, Yinggui Wang
Fine-tuning Large Language Models (LLMs) with downstream data is often considered time-consuming and expensive. Structured pruning methods are primarily employed to improve the inf…
cs.LG2026
LLM-AutoDP: Automatic Data Processing via LLM Agents for Model Fine-tuning
Wei Huang, Anda Cheng, Yinggui Wang +2
Large Language Models (LLMs) can be fine-tuned on domain-specific data to enhance their performance in specialized fields. However, such data often contains numerous low-quality sa…