ReadPaper是深圳学海云帆科技有限公司推出的专业论文阅读平台和学术交流社区,收录近2亿篇论文、近2.7亿位科研论文作者、近3万所高校及研究机构,包括nature、science、cell、pnas、pubmed、arxiv、acl、cvpr等知名期刊会议,涵盖了数学、物理、化学、材料、金融、计算机科
2017. Neural ques- tion generation from text: A preliminary study. CoRR, abs/1704.01792.Qingyu Zhou, Nan Yang, Furu Wei, Chuanqi Tan, Hangbo Bao, and Ming Zhou. 2017. Neural question generation from text: A preliminary study. Lecture Notes in Computer Science, pages 662-671....
Learning to Ask: Neural Question Generation for Reading Comprehension (ACL 2017)将端到端训练的神经网络应用于问题生成,采用 seq2seq+attention 模型架构,摆脱了转换规则与模版的局限,取得了相比于传统方法更好的性能。另一篇将神经网络应用于 QG 的奠基工作 Neural question generation from text: A preliminary s...
1.Learning to ask: Neural question generation for reading comprehension.(ACL2017) 2.Neural question generation from text: A preliminary study.(ACL2017) baseline 三、模型1、Answer-focused Model 作用:将答案编码部分提出来单独解码,生成疑问词2、Position-aware Model ...
Neural question generation from text: A preliminary study.2017NLPcc 三、模型 gated self-attention: 1.计算self matching representation,来源于论文Gated self-matching networks for reading comprehension and question answering.2017ACL 2.输入feature fusion gate,来源于论文Ruminating reader: Reasoning with gated...
Previous work question generation automatically, creates questions from sentences applying syntax and semantic parser. The paper presents a new approach for generating question and answer.doi:10.1007/978-981-15-9774-9_46Sonam SoniPraveen Kumar
Machine Comprehension by Text-to-Text Neural Question Generation Xingdi Yuan, Tong Wang, Caglar Gulcehre, Alessandro Sordoni, Philip Bachman, Sandeep Subramanian, Saizheng Zhang, Adam Trischler RepL4NLP workshop, ACL 2017|July 2017 We propose a recurrent neural model that ...
于是本文提出了用sequence-to-sequence模型来解决问题,即像机器翻译一样,把raw text看成是源语言,把question看成是目标语言,然后相当于是进行翻译。 1.1 推荐历史阅读 Lucy Vanderwende. 2008. The importance of being important: Question generation.https://www.microsoft.com/en-us/research/wp-content/uploads/...
Learning to ask: Neural question generation for reading comprehension. ACL, 2017. paper Xinya Du, Junru Shao, Claire Cardie. Neural question generation from text: A preliminary study. NLPCC, 2017. paper Qingyu Zhou, Nan Yang, Furu Wei, Chuanqi Tan, Hangbo Bao, Ming Zhou. Machine comprehension...
http://bing.comStronger Transformers for Neural Multi-Hop Question Generation字幕版之后会放出,敬请持续关注欢迎加入人工智能机器学习群:556910946,公众号: AI基地,会有视频,资料放送。公众号中输入视频地址或视频ID就可以自助查询对应的字幕版本, 视频播放量 39