1103 papers with code • 24 benchmarks • 45 datasets Few-Shot Learning is an example of meta-learning, where a learner is trained on several related tasks, during the meta-training phase, so that it can generalize well to unseen (but related) tasks with just few examples, during the...
Code Edit pytorch/fairseq official 29,806 fajri91/indommlu 17 Tasks Edit Cross-Lingual Transfer Few-Shot Learning Hate Speech Detection Machine Translation Natural Language Inference Translation Zero-Shot Learning Datasets Edit Introduced in the Paper: XStoryCloze Used in the Paper: SuperGLUE...
Paper:Papers with Code - POODLE: Improving Few-shot Learning via Penalizing Out-of-Distribution SamplesPaper: https://paperswithcode.com/paper/poodle-improving-few-shot-learning-via-1paperswithcode.com/paper/poodle-improving-few-shot-learning-via-1 PDF: https://arxiv.org/pdf/2206.04679v1...
Few-Shot Learning Meta-Learning reinforcement-learning Reinforcement Learning (RL) Datasets Edit mini-Imagenet miniImageNet Results from the Paper Edit Ranked #3 on Few-Shot Image Classification on Mini-Imagenet 20-way (5-shot) Get a GitHub badge TaskDatasetModelMetric NameMetric ValueGlobal ...
Paper Code Simple and Effective Few-Shot Named Entity Recognition with Structured Nearest Neighbor Learning asappresearch/structshot • • EMNLP 2020 We present a simple few-shot named entity recognition (NER) system based on nearest neighbor learning and structured inference....
Zero-Shot Object Counting 2021 Learning To Count Everything code:https://paperswithcode.com/paper/learning-to-count-everything摘要:现有的视觉计数工作主要集中于一个特定的类别,如人、动物和细胞。在本文中,我们感兴趣的是计算所有内容,即计算来自任何类别的对象,只给出来自该类别的少数注释实例。为此,我们将...
这篇paper关注了少样本学习中的训练方式对模型的影响,从本质去探索有没有更高效的方案能够令meta learning所指导的Few-shot Learning(FSL)具有更好的效果。 Episodic learning 首先,我们需要明确什么叫做“Episodic Training”。正如我在之前的论文笔记中提到的那样,元学习在小样本学习中已经获得了比较显著的成果。元学习...
examples from a single task distribution. We choose prompts and hyperparameters for few-shot learning methods using no additional held-out data via methods like cross-validation and minimum description length. The code reproduces the results in ourpaperand supports two forms of few-shot learning: ...
Code for the CVPR 2019 paperFew-Shot Learning with Localization in Realistic Settings. Due to the sheer number of independent moving parts and user-defined parameters, we are providing our code as a series of interactive Jupyter notebooks rather than automated Python scripts. ...
Few-shot learning (FSL) is one of the key future steps in machine learning and raises a lot of attention. In this paper, we focus on the FSL problem of dia