本文整理了基于神经网络的问答系统中，文本生成相关各种算法、优化策略、应用场景的经典论文，以及相关的评估、开源资源等等，需要朋友自取。

资源整理自网络，源地址：https://www.toutiao.com/a1654853707804685

目录

综述论文

1.Recent Advances in Neural Question Generation. arxiv, 2018.

Liangming Pan, Wenqiang Lei, Tat-Seng Chua, Min-Yen Kan.

模型部分

基础Seq2Seq模型

基于Attention机制的序列搭到序列的问题生成模型。

1.Learning to ask: Neural question generation for reading comprehension. ACL, 2017.

Xinya Du, Junru Shao, Claire Cardie.

2.Neural question generation from text: A preliminary study. NLPCC, 2017.

Qingyu Zhou, Nan Yang, Furu Wei, Chuanqi Tan, Hangbo Bao, Ming Zhou.

3.Machine comprehension by text-to-text neural question generation. Rep4NLP@ACL, 2017.

Xingdi Yuan, Tong Wang, Çaglar Gülçehre, Alessandro Sordoni, Philip Bachman, Saizheng Zhang, Sandeep Subramanian, Adam Trischler

问题编码

用于对答案进行编码，以获取更好的问题-答案对应关系的技术。

1.Answer-focused and Position-aware Neural Question Generation. EMNLP, 2018.

Xingwu Sun, Jing Liu, Yajuan Lyu, Wei He, Yanjun Ma, Shi Wang

2.Improving Neural Question Generation Using Answer Separation. AAAI, 2019. code

Yanghoon Kim, Hwanhee Lee, Joongbo Shin, Kyomin Jung.

3.Improving Question Generation with Sentence-level Semantic Matching and Answer Position Inferring. AAAI, 2020.

Xiyao Ma, Qile Zhu, Yanlin Zhou, Xiaolin Li, Dapeng Wu

语言学特征

通过在QG过程中引入语言学特征提升QG的质量。

1.Neural Generation of Diverse Questions using Answer Focus, Contextual and Linguistic Features. INLG, 2018.

Vrindavan Harrison, Marilyn Walker

2.Automatic Question Generation using Relative Pronouns and Adverbs. ACL, 2018.

Payal Khullar, Konigari Rachna, Mukul Hase, Manish Shrivastava

3.Learning to Generate Questions by Learning What not to Generate. WWW, 2019. code

Bang Liu, Mingjun Zhao, Di Niu, Kunfeng Lai, Yancheng He, Haojie Wei, Yu Xu.

4.Improving Neural Question Generation using World Knowledge. arXiv, 2019.

Deepak Gupta, Kaheer Suleman, Mahmoud Adada, Andrew McNamara, Justin Harris

问题相关的Reward

引入强化学习，通过最大化特定的Reward来优化模型训练。

1.Teaching Machines to Ask Questions. IJCAI, 2018.

Kaichun Yao, Libo Zhang, Tiejian Luo, Lili Tao, Yanjun Wu

2.Reinforcement Learning Based Graph-to-Sequence Model for Natural Question Generation arxiv, 2019.

Yu Chen, Lingfei Wu, Mohammed J. Zaki

3.Natural Question Generation with Reinforcement Learning Based Graph-to-Sequence Model NeurIPS Workshop, 2019.

Yu Chen, Lingfei Wu, Mohammed J. Zaki

4.Putting the Horse Before the Cart:A Generator-Evaluator Framework for Question Generation from Text CoNLL, 2019.

Vishwajeet Kumar, Ganesh Ramakrishnan, Yuan-Fang Li

5.Addressing Semantic Drift in Question Generation for Semi-Supervised Question Answering EMNLP, 2019. code

Shiyue Zhang, Mohit Bansal

内容选择

通过选择与答案最相关的内容来优化QG质量。

1.Identifying Where to Focus in Reading Comprehension for Neural Question Generation. EMNLP, 2017.

Xinya Du, Claire Cardie

2.Answer-based Adversarial Training for Generating Clarification Questions. NAACL, 2019. code

Rao S, Daumé III H.

3.Learning to Generate Questions by Learning What not to Generate. WWW, 2019. code

Bang Liu, Mingjun Zhao, Di Niu, Kunfeng Lai, Yancheng He, Haojie Wei, Yu Xu.

4.Improving Question Generation With to the Point Context. EMNLP, 2019.

Jingjing Li, Yifan Gao, Lidong Bing, Irwin King, Michael R. Lyu.

5.Weak Supervision Enhanced Generative Network for Question Generation. IJCAI, 2019.

Yutong Wang, Jiyuan Zheng, Qijiong Liu, Zhou Zhao, Jun Xiao, Yueting Zhuang

6.A Multi-Agent Communication Framework for Question-Worthy Phrase Extraction and Question Generation. AAAI, 2019.

Siyuan Wang, Zhongyu Wei, Zhihao Fan, Yang Liu, Xuanjing Huang

问题类型建模

通过特定的词对QG的问题继续分类，以优化QG。

1.Question Generation for Question Answering. EMNLP,2017.

Nan Duan, Duyu Tang, Peng Chen, Ming Zhou

2.Answer-focused and Position-aware Neural Question Generation. EMNLP, 2018.

Xingwu Sun, Jing Liu, Yajuan Lyu, Wei He, Yanjun Ma, Shi Wang

3.Let Me Know What to Ask: Interrogative-Word-Aware Question Generation EMNLP Workshop, 2019.

Junmo Kang, Haritz Puerto San Roman, Sung-Hyon Myaeng

4.Question-type Driven Question Generation EMNLP, 2019.

Wenjie Zhou, Minghua Zhang, Yunfang Wu

编码上下文信息

引入输入文章的上下文信息来优化QG。

1.Harvesting paragraph-level question-answer pairs from wikipedia. ACL, 2018. code&dataset

Xinya Du, Claire Cardie

2.Leveraging Context Information for Natural Question Generation ACL, 2018. code

Linfeng Song, Zhiguo Wang, Wael Hamza, Yue Zhang, Daniel Gildea

3.Paragraph-level Neural Question Generation with Maxout Pointer and Gated Self-attention Networks. EMNLP, 2018.

Yao Zhao, Xiaochuan Ni, Yuanyuan Ding, Qifa Ke

4.Capturing Greater Context for Question Generation arxiv, 2019.

Luu Anh Tuan, Darsh J Shah, Regina Barzilay

其他方法

1.Cross-Lingual Training for Automatic Question Generation. ACL, 2019. dataset

Vishwajeet Kumar, Nitish Joshi, Arijit Mukherjee, Ganesh Ramakrishnan, Preethi Jyothi

2.Generating Question-Answer Hierarchies. ACL, 2019. code

Kalpesh Krishna and Mohit Iyyer.

3.Unified Language Model Pre-training for Natural Language Understanding and Generation. NeurIPS, 2019. code

Li Dong, Nan Yang, Wenhui Wang, Furu Wei, Xiaodong Liu, Yu Wang, Jianfeng Gao, Ming Zhou, Hsiao-Wuen Hon

4.Can You Unpack That? Learning to Rewrite Questions-in-Context. EMNLP, 2019.

Ahmed Elgohary, Denis Peskov, Jordan L. Boyd-Graber

5.Sequential Copying Networks. AAAI, 2018.

Qingyu Zhou, Nan Yang, Furu Wei, Ming Zhou

应用相关

可控QG的问题

解决问题答案生成过程中人工干预的存在问题。

1.Easy-to-Hard: Leveraging Simple Questions for Complex Question Generation. arxiv, 2019.

Jie Zhao, Xiang Deng, Huan Sun.

2.Difficulty Controllable Generation of Reading Comprehension Questions. IJCAI, 2019.

Yifan Gao, Lidong Bing, Wang Chen, Michael R. Lyu, Irwin King

3.Difficulty-controllable Multi-hop Question Generation From Knowledge Graphs. ISWC, 2019. code&dataset

Vishwajeet Kumar, Yuncheng Hua, Ganesh Ramakrishnan, Guilin Qi, Lianli Gao, Yuan-Fang Li

对话系统中QG

对话系统中，多轮对话中如何生成连贯的问题答案。

1.Learning to Ask Questions in Open-domain Conversational Systems with Typed Decoders. ACL, 2018. codedataset

Yansen Wang, Chenyi Liu, Minlie Huang, Liqiang Nie

2.Interconnected Question Generation with Coreference Alignment and Conversation Flow Modeling. ACL, 2019. code

Yifan Gao, Piji Li, Irwin King, Michael R. Lyu

3.Reinforced Dynamic Reasoning for Conversational Question Generation. ACL, 2019. code dataset

Boyuan Pan, Hao Li, Ziyu Yao, Deng Cai, Huan Sun

4.Towards Answer-unaware Conversational Question Generation. ACL Workshop, 2019.

Mao Nakanishi, Tetsunori Kobayashi, Yoshihiko Hayashi

询问特定问题

探索如何生成特定的类型的问题，比如数学问题，开放性问题，非事实性问题，阐述性问题。

1.Are You Asking the Right Questions? Teaching Machines to Ask Clarification Questions. ACL Workshop, 2017.

Sudha Rao

2.Automatic Opinion Question Generation. ICNLG, 2018.

Yllias Chali, Tina Baghaee

3.A Multi-language Platform for Generating Algebraic Mathematical Word Problems. arxiv, 2019.

Vijini Liyanage, Surangika Ranathunga

4.Asking the Crowd: Question Analysis, Evaluation and Generation for Open Discussion on Online Forums. ACL, 2019.

Zi Chai, Xinyu Xing, Xiaojun Wan, Bo Huang

5.Conclusion-Supplement Answer Generation for Non-Factoid Questions. AAAI, 2020.

Makoto Nakatsuji, Sohei Okui

6.Answer-based Adversarial Training for Generating Clarification Questions. NAACL, 2019. code

Rao S, Daumé III H.

7.Distant Supervised Why-Question Generation with Passage Self-Matching Attention. IJCNN, 2019.

Jiaxin Hu, Zhixu Li, Renshou Wu, Hongling Wang, An Liu, Jiajie Xu, Pengpeng Zhao, Lei Zhao

答案无关QG

在答案无关的QG中，模型需要将问题无关的答案当作回答的主旨。因此，模型需要自动判断问题答案是否在文章当中。

1.Learning to ask: Neural question generation for reading comprehension. ACL, 2017.

Xinya Du, Junru Shao, Claire Cardie.

2.Neural Models for Key Phrase Extraction and Question Generation. ACL Workshop, 2018.

Sandeep Subramanian, Tong Wang, Xingdi Yuan, Saizheng Zhang, Adam Trischler, Yoshua Bengio

3.Self-Attention Architectures for Answer-Agnostic Neural Question Generation. ACL, 2019.

Thomas Scialom, Benjamin Piwowarski, Jacopo Staiano.

无答案QG

处理基于输入文章无法生成答案的问题。

1.Learning to Ask Unanswerable Questions for Machine Reading Comprehension. ACL, 2019.

Haichao Zhu, Li Dong, Furu Wei, Wenhui Wang, Bing Qin, Ting Liu

组合QA和QG

通过联合或多任务学习将QA和QG联合学习。

1.Question Generation for Question Answering. EMNLP,2017.

Nan Duan, Duyu Tang, Peng Chen, Ming Zhou

2.Learning to Collaborate for Question Answering and Asking. NAACL, 2018.

Duyu Tang, Nan Duan, Zhao Yan, Zhirui Zhang, Yibo Sun, Shujie Liu, Yuanhua Lv, Ming Zhou

3.Generating Highly Relevant Questions. EMNLP, 2019.

Jiazuo Qiu, Deyi Xiong

4.Learning to Answer by Learning to Ask: Getting the Best of GPT-2 and BERT Worlds. arxiv, 2019.

Tassilo Klein, Moin Nabi

5.Triple-Joint Modeling for Question Generation Using Cross-Task Autoencoder. NLPCC, 2019.

Hongling Wang, Renshou Wu, Zhixu Li, Zhongqing Wang, Zhigang Chen, Guodong Zhou

6.Addressing Semantic Drift in Question Generation for Semi-Supervised Question Answering EMNLP, 2019. code

Shiyue Zhang, Mohit Bansal

基于知识图谱的QG

将知识图谱引用与QG中技术。

1.Generating Factoid Questions With Recurrent Neural Networks: The 30M Factoid Question-Answer Corpus. ACL, 2016. dataset

Iulian Vlad Serban, Alberto García-Durán, Çaglar Gülçehre, Sungjin Ahn, Sarath Chandar, Aaron C. Courville, Yoshua Bengio

2.Generating Natural Language Question-Answer Pairs from a Knowledge Graph Using a RNN Based Question Generation Model. ACL, 2017.

Mitesh M. Khapra, Dinesh Raghu, Sachindra Joshi, Sathish Reddy

3.Knowledge Questions from Knowledge Graphs. ICTIR, 2017.

Dominic Seyler, Mohamed Yahya, Klaus Berberich.

4.Zero-Shot Question Generation from Knowledge Graphs for Unseen Predicates and Entity Types. NAACL, 2018. code

Hady Elsahar, Christophe Gravier, Frederique Laforest.

5.A Neural Question Generation System Based on Knowledge Base NLPCC, 2018.

Hao Wang, Xiaodong Zhang, Houfeng Wang

6.Formal Query Generation for Question Answering over Knowledge Bases. ESWC, 2018.

Hamid Zafar, Giulio Napolitano, Jens Lehmann

7.Generating Questions for Knowledge Bases via Incorporating Diversified Contexts and Answer-Aware Loss. EMNLP, 2019.

Cao Liu, Kang Liu, Shizhu He, Zaiqing Nie, Jun Zhao

8.Difficulty-controllable Multi-hop Question Generation From Knowledge Graphs. ISWC, 2019. code&dataset

Vishwajeet Kumar, Yuncheng Hua, Ganesh Ramakrishnan, Guilin Qi, Lianli Gao, Yuan-Fang Li

9.How Question Generation Can Help Question Answering over Knowledge Base. NLPCC, 2019.

Sen Hu, Lei Zou, Zhanxing Zhu

可视化问题答案生成

通过一张输入图片生成答案。

1.Generating Natural Questions About an Image ACL, 2016.

Nasrin Mostafazadeh, Ishan Misra, Jacob Devlin, Margaret Mitchell, Xiaodong He, Lucy Vanderwende

2.Creativity: Generating Diverse Questions Using Variational Autoencoders CVPR,2017.

Unnat Jain, Ziyu Zhang, Alexander G. Schwing

3.Automatic Generation of Grounded Visual Questions IJCAI, 2017.

Shijie Zhang, Lizhen Qu, Shaodi You, Zhenglu Yang, Jiawan Zhang

4.A Reinforcement Learning Framework for Natural Question Generation using Bi-discriminators COLING, 2018.

Zhihao Fan, Zhongyu Wei, Siyuan Wang, Yang Liu, Xuanjing Huang

5.Customized Image Narrative Generation via Interactive Visual Question Generation and Answering CVPR, 2018.

Andrew Shin, Yoshitaka Ushiku, Tatsuya Harada

6.Multimodal Differential Network for Visual Question Generation EMNLP, 2018.

Badri Narayana Patro, Sandeep Kumar, Vinod Kumar Kurmi, Vinay P. Namboodiri

7.A Question Type Driven Framework to Diversify Visual Question Generation IJCAI, 2018.

Zhihao Fan, Zhongyu Wei, Piji Li, Yanyan Lan, Xuanjing Huang

8.Visual Question Generation as Dual Task of Visual Question Answering. CVPR, 2018.

Yikang Li, Nan Duan, Bolei Zhou, Xiao Chu, Wanli Ouyang, Xiaogang Wang, Ming Zhou

9.Information Maximizing Visual Question Generation. CVPR, 2019.

Ranjay Krishna, Michael Bernstein, Li Fei-Fei

误导性QG

学习从多个候选问题生成答案。

1.Generating Questions and Multiple-Choice Answers using Semantic Analysis of Texts. COLING, 2016.

Jun Araki, Dheeraj Rajagopal, Sreecharan Sankaranarayanan, Susan Holm, Yukari Yamakawa, Teruko Mitamura

2.Distractor Generation for Multiple Choice Questions Using Learning to Rank. NAACL Workshop, 2018. code

Chen Liang, Xiao Yang, Neisarg Dave, Drew Wham, Bart Pursel, C. Lee Giles

3.Generating Distractors for Reading Comprehension Questions from Real Examinations. AAAI, 2019.

Yifan Gao, Lidong Bing, Piji Li, Irwin King, Michael R. Lyu

评估

问答系统中一个子方向，评估QG生成的质量。

1.Question Asking as Program Generation. NeurIPS, 2017.

Anselm Rothe, Brenden M. Lake, Todd M. Gureckis.

2.Towards a Better Metric for Evaluating Question Generation Systems. EMNLP, 2018.

Preksha Nema, Mitesh M. Khapra.

3.LearningQ: A Large-Scale Dataset for Educational Question Generation. ICWSM, 2018.

Guanliang Chen, Jie Yang, Claudia Hauff, Geert-Jan Houben.

4.Evaluating Rewards for Question Generation Models. NAACL, 2019.

Tom Hosking and Sebastian Riedel.

相关资源

QG相关的数据集和工具。

1.ParaQG: A System for Generating Questions and Answers from Paragraphs. EMNLP Demo, 2019.

Vishwajeet Kumar, Sivaanandh Muneeswaran, Ganesh Ramakrishnan, Yuan-Fang Li.

2.How to Ask Better Questions? A Large-Scale Multi-Domain Dataset for Rewriting Ill-Formed Questions. AAAI, 2020. code

Zewei Chu, Mingda Chen, Jing Chen, Miaosen Wang, Kevin Gimpel, Manaal Faruqui, Xiance Si.