Unverified50% confidenceFactExact time
Parameter-efficient fine-tuning (PEFT) is a class of techniques that adapt to downstream tasks by training only a very small number of newly added or selected parameters, with representative methods including LoRA, prefix tuning, adapters, and so on.
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10/14/2026
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UnverifiedParameter-Efficient Fine-Tuning (PEFT) is the core technical support for achieving low-cost training.79% similarVerifiedParameter-efficient fine-tuning (PEFT) methods such as LoRA and Adapter can compress the number of trainable parameters to less than 1% of the total parameters.76% similarUnverified领域自适应预训练（DAPT）指在通用基础模型上用领域特定语料继续训练，能以较低成本显著提升特定任务性能68% similarUnverified领域适应的标准路径是微调，使用 LoRA 或全量微调对预训练权重进行领域适应，以 WER（词错误率）指标评估效果68% similar
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