首页
移动开发
物联网
服务端
编程语言
企业开发
数据库
业界资讯
其他
搜索
DuoRC: Towards Complex Language Understanding with Paraphrased Reading Comprehension读书笔记
其他
2019-01-29 01:55:02
阅读次数: 0
发表于ACL2018
构建了DuoRC数据集,是一个大规模复杂阅读理解任务,问题和文本的重合度低,且有大量叙述成分需要常识和推理。
猜你喜欢
转载自
blog.csdn.net/sjh18813050566/article/details/86664699
DuoRC: Towards Complex Language Understanding with Paraphrased Reading Comprehension读书笔记
Simple and Effective Multi-Paragraph Reading Comprehension读书笔记
Stochastic Answer Networks for Machine Reading Comprehension读书笔记
Towards Image Understanding From Deep Compression Without Decoding阅读笔记
Photorealistic Text-to-Image Diffusion Models with Deep Language Understanding (Paper reading)
Towards Better Understanding of Document Representation
Watson Natural Language Understanding
Retrieve, Read, Rerank: Towards End-to-End Multi-Document Reading Comprehension
Joint Training of Candidate Extraction and Answer Selection for Reading Comprehension读书笔记
论文笔记 --《Unified Language Model Pre-training for Natural Language Understanding a
【论文笔记】BLIP: Bootstrapping Language-Image Pre-training forUnified Vision-Language Understanding and
Towards Understanding Linear Value Decomposition in Cooperative Multi-Agent Q-Learning 笔记
Create an Azure Language Understanding app
Publish and use a Language Understanding app
什么是Natural Language Understanding(NLU)?
DomainSpecific Language Toolkit: Towards Reusable Libra
Reading and Understanding the Storm UI [Storm UI explained]
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding 论文笔记
论文笔记:BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
【论文笔记】GPT-1:Improving Language Understanding by Generative Pre-Training
【论文笔记】BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
【笔记记录】 BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
NLU(Natural Language Understanding)太难了
What are the major open problems in natural language understanding?
XLNet: Generalized Autoregressive Pretraining for Language Understanding
TinyBERT: Distilling BERT for Natural Language Understanding翻译
Use Azure Speech and Language Understanding Services
Create a Azure Language Understanding Client Application
Shortcut Learning of Large Language Models in Natural Language Understanding: A Survey,2020
Towards Better Understanding of Self-Supervised Representations / Q-Score
今日推荐
周排行
Leetcode简单题61~80
解决zookeeper磁盘IO高的问题
多线程相关方法详解
Maven-setting.xml文件详解
Maven 项目的 classpath 理解
渊亭科技大数据笔试题
配置JVM内存分配
计算机网络个人学习笔记 (三)网络层 :第三部分 连载
js中两个等号(==)和三个等号(===)的区别
用C程序自动打开电脑上的程序
每日归档
更多
2024-09-18(0)
2024-09-17(0)
2024-09-16(0)
2024-09-15(0)
2024-09-14(0)
2024-09-13(0)
2024-09-12(0)
2024-09-11(0)
2024-09-10(0)
2024-09-09(0)