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请查收!顶会AAAI 2020录用论文之自然语言处理篇_aaai与nlp相关的论文

aaai与nlp相关的论文

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导读:人工智能领域顶级会议AAAI 2020持续火爆,共收到有效论文投稿8843篇,其中7737篇论文进入评审环节,最终收录1591篇,收录率为 20.6%。较去年16.2%的收录率,投稿数多了将近1100篇,收录论文数量多了400多篇。本系列文章主要对今年录用的论文按照研究主题进行划分,为相关领域的爱好者们给予便利,省去检索论文的烦恼。本届会议中的优秀论文会在<一起读论文>栏目中进行详细解读,尽请关注!

自然语言处理篇(NLP)

Question Answering

5727: JEC-QA: A Legal-Domain Question Answering Dataset
Haoxi Zhong; Chaojun Xiao; Cunchao Tu; Tianyang Zhang; Zhiyuan Liu; Maosong Sun
Tsinghua University; Powerlaw;

9012: How to Ask Better Questions? A Large-Scale Multi-Domain Dataset for Rewriting Ill-Formed Questions
Zewei Chu; Mingda Chen; Jing Chen; Miaosen Wang; Kevin Gimpel; Manaal Faruqui; Xiance Si
The University of Chicago; Google

9420: QASC: A Dataset for Question Answering via Sentence Composition
Tushar Khot; Peter Clark; Michal Guerquin; Peter Jansen; Ashish Sabharwal
Allen Institute for AI; University of Arizona

1025: CFGNN: Cross Flow Graph Neural Networks for Question Answering on Complex Tables
Xuanyu Zhang
Beijing Normal University

2888: On the Generation of Medical Question-Answer Pairs
Sheng Shen; Yaliang Li; Nan Du; Xian Wu; Yusheng Xie; Shen Ge; Tao Yang; Kai Wang; Xingzheng Liang; Wei Fan
University of California, Berkeley; Alibaba Group; Tencent Medical AI Lab;

2217: Hashing based Answer Selection
Dong Xu; Wu-Jun Li
Nanjing University

9466: TANDA: Transfer and Adapt Pre-Trained Transformer Models for Answer Sentence Selection
Siddhant Garg; Thuy Vu; Alessandro Moschitti
University of Wisconsin-Madison; Amazon;

3296: Capturing Sentence Relations for Answer Sentence Selection with Multi-Perspective Graph Encoding
Zhixing Tian; Yuanzhe Zhang; Xinwei Feng; Wenbin Jiang; Yajuan Lyu ); Kang Liu; Jun Zhao
Chinese Academy of Sciences; Baidu Inc.;

3657: Segment-then-Rank: Non-factoid Question Answering on Instructional Videos
Kyungjae Lee; Nan Duan; Lei Ji; Jason Li; Seungwon Hwang
Yonsei University; Microsoft Research;

3330: Graph-Based Reasoning over Heterogeneous External Knowledge for Commonsense Question Answering
Shangwen Lv; Daya Guo; Jingjing Xu; Duyu Tang; Nan Duan; Ming Gong; Linjun Shou; Daxin Jiang; Guihong Cao; Songlin Hu
Chinese Academy of Sciences; Sun-Yat Sen University; Peking University; Microsoft Research;

3989: An Empirical Study of Content Understanding in Conversational Question Answering
Ting-Rui Chiang; Hao-Tong Ye; Yun-Nung Chen
National Taiwan University

7061: Reasoning with Heterogeneous Graph Alignment for Video Question Answering
Pin Jiang; Yahong Han
Tianjin University

7545: Knowledge and Cross-Pair Pattern Guided Semantic Matching for Question Answering
Zihan Xu; Hai-Tao Zheng; Shaopeng Zhai; Dong Wang
Tsinghua University; Shanghai Jiao Tong university

7752: Neural Question Generation with Answer Pivot
Bingning Wang; Xiaochuan Wang; Ting Yao; Qi Zhang; Jingfang Xu
Sogou Inc.

7778: Getting Closer to AI Complete Question Answering: A Set of Prerequisite Real Tasks
Anna Rogers; Olga Kovaleva; Matthew Downey; Anna Rumshisky
University of Massachusetts Lowell

3333: Hypothetical Answers to Continuous Queries over Data Streams
Luìs Cruz-Filipe; Graça Gaspar; Isabel Nunes
University of Southern Denmark; University of Lisbon

8768: ManyModalQA: Modality Disambiguation and QA over Diverse Inputs
Darryl Hannan; Akshay Jain; Mohit Bansal
University of North Carolina at Chapel Hill

8941: PIQA: Reasoning about Physical Commonsense in Natural Language
Yonatan Bisk; Rowan Zellers; Ronan Le Bras; Jianfeng Gao; Yejin Choi
Carnegie Mellon University; University of Washington; Allen Institute for AI; Microsoft Research

4327: Asking the Right Questions to the Right Users: Active Learning with Imperfect Oracles
Shayok Chakraborty
Florida State University

1192: KnowIT VQA: Answering Knowledge-Based Questions about Videos
Noa Garcia; Mayu Otani; Chenhui Chu; Yuta Nakashima
Osaka University; CyberAgent, Inc.

1305: Overcoming Language Priors in VQA via Decomposed Linguistic Representations
Chenchen Jing; Yuwei WU; Xiaoxun Zhang; Yunde Jia; Qi Wu
Beijing Institute of Technology; Alibaba; University of Adelaide

1655: Divide and Conquer: Question-Guided Spatio-Temporal Contextual Attention for Video Question Answering
Jianwen Jiang; Ziqiang Chen; Haojie Lin; Xibin Zhao; Yue Gao
Tsinghua University

5596: Multi-Question Learning for Visual Question Answering
Chenyi Lei; Lei Wu; Dong Liu; Zhao Li; Guoxin Wang; Haihong Tang; Houqiang Li
Alibaba Group; University of Science and Technology of China;

2069: SG-Net: Syntax-Guided Machine Reading Comprehension
Zhuosheng Zhang; Yuwei Wu; Junru Zhou; Sufeng Duan; Hai Zhao; Rui Wang
Shanghai Jiao Tong University; National Institute of Information and Communications Technology

2547: ReCO: A Large Scale Chinese Reading Comprehension Dataset on Opinion
Bingning Wang; Xiaochuan Wang; Ting Yao; Qi Zhang; Jingfang Xu
Sogou Inc.

6841: A Robust Adversarial Training Approach to Machine Reading Comprehension
Kai Liu; Xin Liu; An Yang; Jing Liu; Jinsong Su; Sujian Li; Qiaoqiao She
Baidu Inc.; Xiamen University; Peking University

2771: DCMN+: Dual Co-Matching Network for Multi-choice Reading Comprehension
Shuiliang Zhang; Hai Zhao; Yuwei Wu; Zhuosheng Zhang; Xi Zhou; Xiang Zhou
Shanghai Jiao Tong University; CloudWalk Technology

8319: Translucent Answer Predictions in Multi-Hop Reading Comprehension
G P Shrivatsa Bhargav; Michael R. Glass; Dinesh Garg; Shirish Shevade; Saswati Dana; Dinesh Khandelwal; L Venkata Subramaniam; Alfio Gliozzo
Indian Institute of Science; IBM Research AI;

9384: Select, Answer and Explain: Interpretable Multi-hop Reading Comprehension over Multiple Documents
Ming Tu; Kevin Huang; Guangtao Wang; Jing Huang; Xiaodong He; Bowen Zhou
JD AI Research

7388: Co-Attention Hierarchical Network: Generating Coherent Long Distractors for Reading Comprehension
Xiaorui Zhou; Senlin Luo; Yunfang Wu
Beijing Institute of Technology; Peking University

2519: Multi-Task Learning with Generative Adversarial Training for Multi-Passage Machine Reading Comprehension
Qiyu Ren; Xiang Cheng; Sen Su
Beijing University of Posts and Telecommunications

3066: Unsupervised Domain Adaptation on Reading Comprehension
Yu Cao; Meng Fang; Joey Tianyi Zhou; Baosheng Yu
University of Sydney; Tencent AI Lab; A*STAR

6979: MMM: Multi-stage Multi-task Learning for Multi-choice Reading Comprehension
Di Jin; Shuyang Gao; Jiun-Yu Kao; Tagyoung Chung; Dilek Hakkani-tur
MIT; Amazon;

7755: Assessing the Benchmarking Capacity of Machine Reading Comprehension Datasets
Saku Sugawara; Pontus Stenetorp; Kentaro Inui; Akiko Aizawa
University of Tokyo; Tohoku University; National Institute of Informatics

3142: Attentive User-Engaged Adversarial Neural Network for Community Question Answering
Yuexiang Xie; Ying Shen; Yaliang Li; Min Yang; Kai Lei
Peking University; Alibaba Group; Chinese Academy of Sciences

5372: Joint Learning of Answer Selection and Answer Summary Generation in Community Question Answering
Yang Deng; Wai Lam; Yuexiang Xie; Daoyuan Chen; Yaliang Li; Min Yang; Ying Shen
The Chinese University of Hong Kong; Peking University; Alibaba Group;

3512: Improving Question Generation with Sentence-level Semantic Matching and Answer Position Inferring
Xiyao Ma; Qile Zhu; Yanlin Zhou; Xiaolin Li
University of Florida; Tongdun Technology

3858: Conclusion-Supplement Answer Generation for Non-Factoid Questions
Makoto Nakatsuji; Sohei Okui
NTT

4189: Visual Dialogue State Tracking for Question Generation
Wei Pang; Xiaojie Wang
Beijing University of Posts and Telecommunications

5371: Location-aware Graph Convolutional Networks for Video Question Answering
Deng Huang; Peihao Chen; Runhao Zeng; Qing Du; Mingkui Tan; Chuang Gan
South China University of Technology; MIT-Watson AI Lab

4656: Generating Well-formed Answers by Machine Reading with Stochastic Selector Networks
Bin Bi; Chen Wu; Ming Yan; Wei Wang; Jiangnan Xia; Chenliang Li
Alibaba Group;

8678: Capturing Greater Context for Question Generation
Anh Tuan Luu; Darsh Shah; Regina Barzilay
MIT CSAIL

Sequence Labeling

1075: Knowledge-Graph Augmented Word Representations For Named Entity Recognition
Qizhen He; Liang Wu; Yida Yin; Heming Cai
Bilibili.com

1834: Leveraging Multi-token Entities in Document-level Named Entity Recognition
Anwen Hu; Zhicheng Dou; Ji-Rong Wen; Jian-Yun Nie
Renming University of China; Université de Montréal

2531: Fine-Grained Named Entity Typing over Distantly Supervised Data Based on Refined Representations
Muhammad Asif Ali; Yifang Sun; Bing Li; Wei Wang
University of New South Wales

3325: Boundary Enhanced Neural Span Classification for Nested Named Entity Recognition
Chuanqi Tan; Wei Qiu; Mosha Chen; Rui Wang; Fei Huang
Alibaba Inc.

5015: Enhanced Meta-Learning for Cross-lingual Named Entity Recognition with Minimal Resources
Qianhui Wu; Zijia Lin; Guoxin Wang; Hui Chen; Borje Karlsson; Biqing Huang; Chin-Yew Lin
Tsinghua University; Microsoft;

5916: Robust Named Entity Recognition with Truecasing Pretraining
Stephen Mayhew; Nitish Gupta; Dan Roth
University of Pennsylvania

6346: HAMNER: Headword Amplified Multi-span Distantly Supervised Method for Domain Specific Named Entity Recognition
Shifeng Liu; Yifang Sun; Bing Li; Wei Wang; Xiang Zhao
University of New South Wales; National University of Defence Technology

7327: Hierarchical Contextualized Representation for Named Entity Recognition
Ying Luo; Fengshun Xiao; Hai Zhao
Shanghai Jiiao Tong University

7577: Zero-Resource Cross-Lingual Named Entity Recognition
M SAIFUL BARI; Shafiq Joty; Prathyusha Jwalapuram
Nanyang Technological University

9947: Recursively Binary Modification Model for Nested Named Entity Recognition
Bing Li; Shifeng Liu; Yifang Sun; Wei Wang; Xiang Zhao
University of New South Wales; National University of Defence Technology

9303: Low Resource Sequence Tagging with Weak Labels
Edwin Simpson; Jonas Pfeiffer; Iryna Gurevych
TU-Darmstadt; Darmstadt University

8857: Weakly Supervised Sequence Tagging from Noisy Rules
Esteban Safranchik; Shiying Luo; Stephen Bach
Brown University

8406: Semi-Supervised Learning on Meta Structure: Multi-Task Tagging and Parsing in Low-Resource Scenarios
KyungTae Lim; Jay-Yoon Lee; Jaime Carbonell; Thierry Poibeau
LATTICE; Carnegie Mellon University

Semantics and Summar

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