In the paper, we report the results for the NLPCC2021 shared-task of Few-shot Learning for Chinese NLP. This shared task is proposed in the context of pre-trained language models, where models only have access to limited human-labeled data. The goal of the task is to compare different ...
通过metric learningsiamese networkSiamese Neural Networks for One-shot Image RecognitionKNNMatching Networks for One Shot LearningBregman散度(平方欧氏距离和Mahalanobis距离)Prototypical Networks fo…
nlp、大模型31 人赞同了该文章 目录 收起 一、背景 二、技术方案 1.few-shot 介绍 2.meta-learning介绍 三、实验 zero-shot 和 few-shot (Random labels 、gold labels) 对比 meta-learning random labels correct 提示few-shot数量 manual templates out-of-distribution (OOD) text 总结 论文解读——带...
Few-shot learning (FSL) is one of the key future steps in machine learning and has raised a lot of attention. However, in contrast to the rapid development in other domains, such as Computer Vision, the progress of FSL in Nature Language Processing (NLP) is much slower. One of the key...
nlp few-shot-learning sentence-transformers Updated Sep 19, 2024 Jupyter Notebook tristandeleu / pytorch-meta Star 2k Code Issues Pull requests A collection of extensions and data-loaders for few-shot learning & meta-learning in PyTorch pytorch meta-learning few-shot-learning Updated Jul ...
Few-shot learning-the ability to train models with access to limited data-has become increasingly popular in the natural language processing (NLP) domain, as large language models such as GPT and T0 have been empirically shown to achieve high performance in numerous tasks with access to just a...
nlpdeep-learningpromptpytorchinformation-extractionknowledge-graphnamed-entity-recognitionchinesenermulti-modalkgrelation-extractionlightnerfew-shotlow-resourcedocument-levelattribute-extractionknowpromptdeepkeinstructie UpdatedNov 3, 2024 Python learnables/learn2learn ...
Fe本质上可以在一定程度上“修改”LLM的思考方向,使LLM能够在Few-shot CoT语境下生成中间样本。 在大多数情况下,每个Fe链包含多个Fe示例,以更全面地覆盖不同场景。在这种情况下,多个节点被用作当前迭代轮次的输入提示组件,以帮助LLM更好地学习多个分段策略。由于每个模块的搜索空间大且样本多样性高,这种Few-shot Co...
摘要: Due to the limited length and freely constructed sentence structures, it is a difficult classification task for short text classification. In this paper, a short text classification framework based...关键词: Convolutional neural networks Deep learning Few-shot learning Text classification ...
few-shot learning,这里shot 有计量的意思,指少样本学习,机器学习模型在学习了一定类别的大量数据后,对于新的类别,只需要少量的样本就能快速学习,对应的有one-shot learning, 一样本学习,也算样本少到为一的情况下的一种few-shot learning, 这里的少样本学习的研究领域与迁移学习有一大部分交集部分,即在源域有足够...