牛哥精选 · 一年

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🤖 AI·大模型 arXiv NLP 2026-05-20

Rethinking 1-bit Optimization Leveraging Pre-trained Large Language Models

颠覆传统，用预训练大模型突破1-bit量化瓶颈，既省存储又保精度。

arXiv:2508.06974v2 Announce Type: replace Abstract: 1-bit LLM quantization offers significant advantages in reducing storage and computational costs. …

1-bit量化大语言模型预训练模型渐进式优化训练成本

📝 深度技术 arXiv 机器学习 2026-05-19

Rethinking Output Alignment For 1-bit Post-Training Quantization of Large Language Models

1-bit量化大模型新思路，输出对齐策略再审视，助力低资源设备高效推理

arXiv:2512.21651v3 Announce Type: replace Abstract: Large Language Models (LLMs) deliver strong performance across a wide range of NLP tasks, but thei…

llm 1-bit量化后训练量化输出对齐模型压缩

📅 日期

2026-05-20 2026-05-19

🐂 牛哥精选

Rethinking 1-bit Optimization Leveraging Pre-trained Large Language Models

Rethinking Output Alignment For 1-bit Post-Training Quantization of Large Language Models

📅 日期