[](Top 6 Open Source Pretrained Models for Text Classification you should use.assets/XLNet_Perf.png) 论文链接: XLNet: Generalized Autoregressive Pretraining for Language Understanding Github链接:https://github.com/zihangdai/xlnet 预训练模型 #2: ERNIE 尽管ERNIE 1.0(发布于2019年3月)一直是文本分类的...
[](Top 6 Open Source Pretrained Models for Text Classification you should use.assets/XLNet_Perf.png) 论文链接: XLNet: Generalized Autoregressive Pretraining for Language Understanding Github链接: https://github.com/zihangdai/xlnet 预训练模型 #2: ERNIE 尽管ERNIE 1.0(发布于2019年3月)一直是文本分类...
1). These models try to learn feature representations and perform classification (or regression), in an end-to-end fashion. 2). They not only have the ability to uncover hidden patterns in data, but also are much more transferable from one application to another. 基于深度学习的文本分析方法...
Convolutional neural networks for sentence classification 2014,该方法首次将CNN 结构用于文本分类,但是该模型无法避免使用 CNN 中固定窗口的缺点,因此无法建模更长的序列信息。(该缺点已解决) TextRCNN模型 Recurrent convolutional neural networks for text classification 2015,该方法主要针对传统分类方法存在着忽略上下文...
深度网络方法(Deep Learning Models) 浅层网络模型(Shallow Learning Models) 数据集(Datasets) 评估方式(Evaluation Metrics) 展望研究与挑战(Future Research Challenges) 实用工具与资料(Tools and Repos) Github地址:https://github.com/xiaoqian19940510/text-classification-surveys ...
demonstrates a set of attention-based models for long-text classification: LTR methods process the input in chunks from left to right and are suitable for auto-regressive applications. Sparse methods mostly reduce the computational order to O(n) by avoiding a full quadratic attention matrix ...
雷锋网 AI 科技评论按,近日,斯坦福自然语言处理小组发布了一篇博文,重点讨论了由 Ribeiro、Marco Tulio、Sameer Singh 和 Carlos Guestrin 写的论文「Semantically equivalent adversarial rules for debugging nlp models」(用于调试 NLP 模型的语义等价对立规则)。该论文是 2018 年 ACL 论文,被发表在《计算语言学协会第...
无监督方法——EDA来自论文《EDA: Easy Data Augmentation Techniques for Boosting Performance on Text Classification Tasks》。一个用于提高文本分类任务性能的简单数据增强技术。 EDA 由四个简单但功能强大的操作组成:同义词替换、随机插入、随机交换和随机删除。 在实验的五个文本分类任务中,EDA 提高了卷积和递归神经...
utm_source=blog&utm_medium=top-pretrained-models-nlp-articleULMFiT 的预训练模型:https://www.paperswithcode.com/paper/universal-language-model-fine-tuning-for-text研究论文:https://arxiv.org/abs/1801.06146 Transformer GitHub 项目地址:https://github.com/tensorflow/models/tree/master/official/...
继续NLP保姆级教程系列,今天的教程是基于FAIR的Bag of Tricks for Efficient Text Classification[1]。也就是我们常说的fastText。 最让人欣喜的这篇论文配套提供了fasttext工具包。这个工具包代码质量非常高,论文结果一键还原,目前已经是包装地非常专业了,这是fastText官网和其github代码库,以及提供了python接口,可以直接...