Unverified50% confidenceFactExact time
Common means of domain adaptation include: continued pre-training or fine-tuning on in-domain corpora, introducing domain dictionaries or glossaries, and using a small amount of labeled data for parameter-efficient fine-tuning.
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Long-term
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10/31/2026
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UnverifiedDomain fine-tuning refers to supervised fine-tuning or preference optimization of a general pretrained base model using high-quality data from a specific domain, requiring less data and enabling faster iteration compared to training from scratch.75% similarUnverifiedPretrained classifiers are typically designed for fixed category systems, and when facing entirely new domains or highly specialized tasks may require fine-tuning or even retraining, and cannot replace large models in complex semantic understanding and generation.74% 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74% 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72% similar
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