[](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...
5、Universal Language Model Fine-tuning for Text Classification (ULMFit) 6、Learned in Translation- Contextualized Word Vectors (Cove) 7、Deepcontextualized word representations (ELMO) 8、Improving Language Understanding by Generative Pre-Training (GPT) 9、Language Modelsare Unsupervised Multitask Learners ...
http://www.wildml.com/2015/12/implementing-a-cnn-for-text-classification-in-tensorflow/ 由于该文章是纯英文的,某些读者可能还不习惯阅读这类文献,我下面结合一张神经网络设计图,来说明本文中所使用的神经网络,具体设计图(又是手画图,囧)如下: 简要介绍下上面的图,第一层数据输入层,将文本序列展开成词向量...
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 全文五万字,分几篇整理,后续会整理成PDF分享给大家,欢迎持续关注!
Towards a Robust Deep Neural Network in Text Domain A Survey. Wenqi Wang, Lina Wang, Benxiao Tang, Run Wang, Aoshuang Ye. 2019. Adversarial Attacks on Deep Learning Models in Natural Language Processing: A Survey. Wei Emma Zhang, Quan Z. Sheng, Ahoud Alhazmi, Chenliang Li. 2019. ...
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...
一个自然的想法是像论文Adversarial Training Methods for Semi-Supervised Text Classification一样,将扰动加到 Embedding 层 Because the set of high-dimensional one-hot vectors does not admit infinitesimal perturbation, we define the perturbation on continuous word embeddings instead of discrete word inputs....
Fine-Tune BERT for Spam Classification Now we will fine-tune a BERT model to perform text classification with the help of the Transformers library. You should have a basic understanding of defining, training, and evaluating neural network models in PyTorch. If you want a quick refresher ...
[NLP] TextCNN模型原理和实现 回到顶部 1. 模型原理 1.1 论文 Yoon Kim在论文(2014 EMNLP) Convolutional Neural Networks for Sentence Classification提出TextCNN。 将卷积神经网络CNN应用到文本分类任务,利用多个不同size的kernel来提取句子中的关键信息(类似于多窗口大小的ngram),从而能够更好地捕捉局部相关性。