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📝 深度技术 arXiv AI 2026-08-04

F-WANDA: Fisher-Reweighted Post-Training Pruning for Sustainable Deployment of Large Language Models

Fisher重加权剪枝，让大模型压缩更省能耗，部署更可持续。

arXiv:2608.00481v1 Announce Type: new Abstract: One-shot post-training pruning is the most energy-frugal compression strategy for largelanguage models…

大模型模型剪枝 fisher加权后训练压缩可持续ai

📝 深度技术 arXiv 计算机视觉 2026-07-24

C-PTQ: Fisher-weighted Channel-wise Sensitivity for Post-training Quantization of MLLMs

Fisher信息加权通道敏感度，为多模态大模型后训练量化提供新高效方案。

arXiv:2607.21076v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) require huge memory and computational costs, which limits the…

多模态大语言模型后训练量化 fisher加权通道敏感度模型压缩

📅 日期

2026-05-20 2026-05-19

🐂 牛哥精选

F-WANDA: Fisher-Reweighted Post-Training Pruning for Sustainable Deployment of Large Language Models

C-PTQ: Fisher-weighted Channel-wise Sensitivity for Post-training Quantization of MLLMs

📅 日期