自然语言处理学习——用GAN进行文本生成之一些总结性的介绍

Github 项目推荐 | PyTorch 实现的 GAN（有相当多的GAN模型）  Github项目地址：https://github.com/eriklindernoren/PyTorch-GAN

Github 项目推荐 | PyTorch 实现的 GAN 文本生成框架  Github项目地址：https://github.com/williamSYSU/TextGAN-PyTorch

然后对于gan的一个简单的introduction的代码： https://github.com/tanayag/gans

GAN在自然语言处理方面有哪些有趣的文章和应用？ 

GAN for NLP (论文笔记及解读) 

GAN+Text对抗文本生成paperReading

Role of RL in Text Generation by GAN(强化学习在生成对抗网络文本生成中扮演的角色) 

一些论文 《Generating Text via Adversarial Training》

GAN+文本生成：让文本以假乱真（上） 

为什么不能用GAN来干NLP 

 

关于文档摘要的一些 链接 

https://github.com/OctoberChang/awesome-text-summarization

https://github.com/luopeixiang/awesome-text-summarization#sentence-summarization

https://github.com/r3ntru3w4n9/brief

https://github.com/iwangjian/textsum-gan

论文 https://www.aaai.org/ocs/index.php/AAAI/AAAI18/paper/view/16238/16492

Generative Adversarial Network for Abstractive Text Summarization github

Generative Adversarial Network with Policy Gradient for Text Summarization

https://github.com/rohithreddy024/Text-Summarizer-Pytorch

Python 自然语言处理 https://github.com/zhuyuanxiang/NLTK-Python-CN

Python 自然语言处理 第二版 https://usyiyi.github.io/nlp-py-2e-zh/

一些论文：

 Long Text Generation via Adversarial Training with Leaked Information https://arxiv.org/pdf/1709.08624.pdf

Learning to Encode Text as Human-Readable Summaries using Generative Adversarial Networks https://arxiv.org/pdf/1810.02851.pdf

Unparalleled Text summarization using GAN https://github.com/yaushian/Unparalleled-Text-Summarization-using-GAN

Adversarial Text Generation via Feature-Mover’s Distance https://papers.nips.cc/paper/2018/file/074177d3eb6371e32c16c55a3b8f706b-Paper.pdf

 

Summarization https://github.com/sebastianruder/NLP-progress/blob/master/english/summarization.md

文本摘要简述 https://www.jiqizhixin.com/articles/2019-03-25-7

 

文本情感分类 更好的损失函数 https://kexue.fm/archives/4293

 

 

文本 摘要的方法：

information redundancy text Summarization github

https://github.com/vishnu45/NLP-Extractive-NEWS-summarization-using-MMR

https://medium.com/tech-that-works/maximal-marginal-relevance-to-rerank-results-in-unsupervised-keyphrase-extraction-22d95015c7c5

文本摘要生成的库 https://github.com/miso-belica/sumy

InfoGAN  https://arxiv.org/pdf/1606.03657.pdf

https://towardsdatascience.com/build-infogan-from-scratch-f20ee85cba03 

https://machinelearningmastery.com/how-to-develop-an-information-maximizing-generative-adversarial-network-infogan-in-keras/

（可解释的生成对抗网络：InfoGAN的通俗解释）https://zhuanlan.zhihu.com/p/55945164

GAN+BERT的结合（ICLR 2020 | BERT还能跟GAN结合？ELECTRA来了！）

SiGAN: Siamese Generative Adversarial Network for Identity-Preserving Face Hallucination

CS-NET at SemEval-2020 Task 4: Siamese BERT for ComVE

关于MiniMAX的loss https://discuss.pytorch.org/t/minmax-adversarial-loss/89865/2

 

 

标签：总结性,github,Text,文本,GAN,https,自然语言,com
来源： https://blog.51cto.com/u_12136715/2952814