例如,在问答任务中,可以使用few-shot learning技术来训练模型,使其能够根据少量示例问题和答案来回答新的问题。通过微调预训练的语言模型,可以使其适应这种任务,从而在只有少量示例的情况下获得良好的性能。 总之,"true few-shot learning with language models"指的是使用预训练的语言模型进行真正的few-shot学习,通过...
此文试图将这种能力迁移到多模态场景之下,通过一个图像编码器将图像转换为连续的嵌入序列,作为一种prompt,与文本信息一起送入语言模型中。在多个few-shot场景下的测试表明,此文的算法在多模态少样本情况下表现出比基线较好的效果。 Motivation 大规模的预训练transformer模型在少样本情况下可以表现出良好的效果,例...
Frozen achieves the necessary capacities to some degree, but a key limitation is that it achieves far from state-of-the-art performance on the specific tasks that it learns in a few shots, compared to systems that use the full training set for those tasks. As such, the main contribution o...
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Atlas: Few-shot Learning with Retrieval Augmented Language Models Aug 2022 Gautier Izacard, Patrick Lewis等 [Meta AI Research等] https://arxiv.org/abs/2208.03299 https://github.com/facebookresearch/atlas 大型语言模型在广泛的任务中显示出令人印象深刻的few-shot结果。然而,当知识是这些结果的关键时,...
True Few-Shot Learning with Language ModelsEthan PerezDouwe KielaKyunghyun Cho
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performance on the specific tasks that it learns in a few shots, compared to systems that use the full training set for thosetasks. As such, the main contribution of this work should be seen as a starting point or baseline for this exciting area of research of multimodal few-shot learning...
By presenting a broad characterization of GPT-3’s strengths and weaknesses, including these limitations, we hope to stimulate study of few-shot learning in language models and draw attention to where progress is most needed. A heuristic sense of the overall results can be seen in Figure 1.3...
【1】Meta-learning for Few-shot Natural Language Processing: A Survey 摘要：少样本自然语言处理（...