Unverified50% confidenceFactExact time
Zero-shot Learning refers to a model's ability to complete new tasks solely based on general knowledge accumulated during the pre-training phase, without having been trained on those specific tasks.
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9/10/2026
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VerifiedOne-shot learning is not the same as zero-shot learning; the single demonstration relies on prior knowledge accumulated by the model from massive pretraining data.79% similarVerifiedFew-Shot Learning refers to providing a small number of examples (typically 2–8) in the prompt, allowing the model to complete new tasks through analogical reasoning.76% similarUnverifiedFew-shot Learning相比全量微调的优势在于零训练成本和即时切换能力，只需更换几个示例即可调整品牌语气74% similarUnverifiedControlNet's zero convolution layer design (initialized with zero weights) ensures that the original model's capabilities are not disrupted during early training, with training costs far lower than training a new model from scratch.74% similarUnverifiedVLM能够根据自然语言描述识别训练数据中从未出现的目标类别，这种能力被称为零样本（zero-shot）或开放词汇（open-vocabulary）识别72% similar
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