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This paper describes the design and implementation of a new machine learning model for online learning systems.
Experiments with a deductive question-answering program
James R. Slagle. 1965 · 1965
Earlier work this paper cites.
A review of methods for automatic understanding of natural language mathematical problems
Anirban Mukherjee and Utpal Garain. 2008 · 2008
Earlier work this paper cites.
Chinese Semantic Role Labeling with Shallow Parsing. In Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing, EMNLP 2009 . 1475–1483
Weiwei Sun, Zhifang Sui, Meng Wang, and Xin Wang. 2009 · 2009
Earlier work this paper cites.
Mining Heterogeneous Information Networks: Principles and Methodologies
Yizhou Sun and Jiawei Han. 2012 · 2012
Earlier work this paper cites.
Scaling Semantic Parsers with On-the-Fly Ontology Matching. In Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing, EMNLP 2013 . 1545–1556
Tom Kwiatkowski, Eunsol Choi, Yoav Artzi, and Luke S. Zettlemoyer. 2013 · 2013
Earlier work this paper cites.
Engaging with massive online courses. In 23rd International World Wide Web Conference, WWW ’14 . 687–698
Ashton Anderson, Daniel P. Huttenlocher, Jon M. Kleinberg, and Jure Leskovec. 2014 · 2014
Earlier work this paper cites.
Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation. In Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing, EMNLP 2014 . 1724–1734
Kyunghyun Cho, Bart van Merrienboer, Çaglar Gülçehre, Dzmitry Bahdanau, Fethi Bougares, Holger Schwenk, and Yoshua Bengio. 2014 · 2014
Earlier work this paper cites.
Learning from natural instructions
Dan Goldwasser and Dan Roth. 2014 · 2014
Earlier work this paper cites.
Learning to Solve Arithmetic Word Problems with Verb Categorization. In Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing, EMNLP 2014 . 523–533
Mohammad Javad Hosseini, Hannaneh Hajishirzi, Oren Etzioni, and Nate Kushman. 2014 · 2014
Earlier work this paper cites.
Learning to Automatically Solve Algebra Word Problems. In Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics, ACL 2014 . 271–281
Nate Kushman, Luke Zettlemoyer, Regina Barzilay, and Yoav Artzi. 2014 · 2014
Earlier work this paper cites.
Adam: A Method for Stochastic Optimization. In 3rd International Conference on Learning Representations, ICLR 2015
Diederik P. Kingma and Jimmy Ba. 2015 · 2015
Earlier work this paper cites.
Parsing Algebraic Word Problems into Equations
Rik Koncel-Kedziorski, Hannaneh Hajishirzi, Ashish Sabharwal, Oren Etzioni, and Siena Dumas Ang. 2015 · 2015
Earlier work this paper cites.
Solving General Arithmetic Word Problems. In Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing, EMNLP 2015 . 1743–1752
Subhro Roy and Dan Roth. 2015 · 2015
Earlier work this paper cites.
Automatically Solving Number Word Problems by Semantic Parsing and Reasoning. In Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing, EMNLP 2015 . 1132–1142
Shuming Shi, Yuehui Wang, Chin-Yew Lin, Xiaojiang Liu, and Yong Rui. 2015 · 2015
Earlier work this paper cites.
MAWPS: A Math Word Problem Repository. In NAACL HLT 2016, The 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies . 1152–1157
Rik Koncel-Kedziorski, Subhro Roy, Aida Amini, Nate Kushman, and Hannaneh Hajishirzi. 2016 · 2016
Earlier work this paper cites.
Deep Biaffine Attention for Neural Dependency Parsing. In 5th International Conference on Learning Representations, ICLR 2017
Timothy Dozat and Christopher D. Manning. 2017 · 2017
Earlier work this paper cites.
Learning Fine-Grained Expressions to Solve Math Word Problems. In Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, EMNLP 2017 . 805–814
Danqing Huang, Shuming Shi, Chin-Yew Lin, and Jian Yin. 2017 · 2017
Cited alongside, same era.
Deep Neural Solver for Math Word Problems. In Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, EMNLP 2017 . 845–854
Yan Wang, Xiaojiang Liu, and Shuming Shi. 2017 · 2017
Cited alongside, same era.
Neural Math Word Problem Solver with Reinforcement Learning. In Proceedings of the 27th International Conference on Computational Linguistics, COLING 2018 . 213–223
Danqing Huang, Jing Liu, Chin-Yew Lin, and Jian Yin. 2018 · 2018
Cited alongside, same era.
Finding Similar Exercises in Online Education Systems. In Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, KDD 2018 . 1821–1830
Qi Liu, Zai Huang, Zhenya Huang, Chuanren Liu, Enhong Chen, Yu Su, and Guoping Hu. 2018 · 2018
Cited alongside, same era.
A Goal-Driven Tree-Structured Neural Model for Math Word Problems. In Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, IJCAI 2019 . 5299–5305
Zhipeng Xie and Shichao Sun. 2019 · 2019
Later among the works it cites.
Heterogeneous Graph Neural Network. In Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, KDD 2019 . 793–803
Chuxu Zhang, Dongjin Song, Chao Huang, Ananthram Swami, and Nitesh V. Chawla. 2019 · 2019
Later among the works it cites.
Graph Transformer for Graph-to-Sequence Learning. In The Thirty-Fourth AAAI Conference on Artificial Intelligence, AAAI 2020 . 7464–7471
Deng Cai and Wai Lam. 2020 · 2020
Later among the works it cites.
N-LTP: A Open-source Neural Chinese Language Technology Platform with Pretrained Models
Wanxiang Che, Yunlong Feng, Libo Qin, and Ting Liu. 2020 · 2020
Later among the works it cites.
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Know What You Don’t Know: Unanswerable Questions for SQuAD. In Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics . 784–789
Pranav Rajpurkar, Robin Jia, and Percy Liang. 2018 · 2018
Cited alongside, same era.
Mapping to Declarative Knowledge for Word Problem Solving
Subhro Roy and Dan Roth. 2018 · 2018
Cited alongside, same era.
Modeling Relational Data with Graph Convolutional Networks. In The Semantic Web - 15th International Conference, ESWC 2018 (Lecture Notes in Computer Science, Vol. 10843) . 593–607
Michael Sejr Schlichtkrull, Thomas N. Kipf, Peter Bloem, Rianne van den Berg, Ivan Titov, and Max Welling. 2018 · 2018
Cited alongside, same era.
Translating Math Word Problem to Expression Tree. In Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, EMNLP 2018 . 1064–1069
Lei Wang, Yan Wang, Deng Cai, Dongxiang Zhang, and Xiaojiang Liu. 2018 · 2018
Cited alongside, same era.
QANet: Combining Local Convolution with Global Self-Attention for Reading Comprehension. In 6th International Conference on Learning Representations, ICLR 2018
Adams Wei Yu, David Dohan, Minh-Thang Luong, Rui Zhao, Kai Chen, Mohammad Norouzi, and Quoc V. Le. 2018 · 2018
Cited alongside, same era.
Supervised Community Detection with Line Graph Neural Networks. In 7th International Conference on Learning Representations, ICLR 2019
Zhengdao Chen, Lisha Li, and Joan Bruna. 2019 · 2019
Cited alongside, same era.
Semantically-Aligned Equation Generation for Solving and Reasoning Math Word Problems. In Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL-HLT 2019 . 2656–2668
Ting-Rui Chiang and Yun-Nung Chen. 2019 · 2019
Cited alongside, same era.
DROP: A Reading Comprehension Benchmark Requiring Discrete Reasoning Over Paragraphs. In Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies . 2368–2378
Dheeru Dua, Yizhong Wang, Pradeep Dasigi, Gabriel Stanovsky, Sameer Singh, and Matt Gardner. 2019 · 2019
Cited alongside, same era.
Measuring and Relieving the Over-Smoothing Problem for Graph Neural Networks from the Topological View. In The Thirty-Fourth AAAI Conference on Artificial Intelligence, AAAI 2020 . 3438–3445
Deli Chen, Yankai Lin, Wei Li, Peng Li, Jie Zhou, and Xu Sun. 2020a · 2020
Later among the works it cites.
Question Directed Graph Attention Network for Numerical Reasoning over Text. In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, EMNLP 2020 . 6759–6768
Kunlong Chen, Weidi Xu, Xingyi Cheng, Zou Xiaochuan, Yuyu Zhang, Le Song, Taifeng Wang, Yuan Qi, and Wei Chu. 2020b · 2020
Later among the works it cites.
HanLP: Han Language Processing
Han He. 2020 · 2020
Later among the works it cites.
Heterogeneous Graph Transformer. In WWW ’20: The Web Conference 2020 . 2704–2710
Ziniu Hu, Yuxiao Dong, Kuansan Wang, and Yizhou Sun. 2020 · 2020
Later among the works it cites.
Solving Math Word Problems with Multi-Encoders and Multi-Decoders. In Proceedings of the 28th International Conference on Computational Linguistics, COLING 2020 . 2924–2934
Yibin Shen and Cheqing Jin. 2020 · 2020
Later among the works it cites.
RAT-SQL: Relation-Aware Schema Encoding and Linking for Text-to-SQL Parsers. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, ACL 2020 . 7567–7578
Bailin Wang, Richard Shin, Xiaodong Liu, Oleksandr Polozov, and Matthew Richardson. 2020 · 2020
Later among the works it cites.
Graph-to-Tree Learning for Solving Math Word Problems. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, ACL 2020 . 3928–3937
Jipeng Zhang, Lei Wang, Roy Ka-Wei Lee, Yi Bin, Yan Wang, Jie Shao, and Ee-Peng Lim. 2020 · 2020
Later among the works it cites.
Ape210K: A Large-Scale and Template-Rich Dataset of Math Word Problems
Wei Zhao, Mingyue Shang, Yang Liu, Liang Wang, and Jingming Liu. 2020b · 2020
Later among the works it cites.
Line Graph Enhanced AMR-to-Text Generation with Mix-Order Graph Attention Networks. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, ACL 2020 . 732–741
Yanbin Zhao, Lu Chen, Zhi Chen, Ruisheng Cao, Su Zhu, and Kai Yu. 2020a · 2020
Later among the works it cites.
HMS: A Hierarchical Solver with Dependency-Enhanced Understanding for Math Word Problem. In Thirty-Fifth AAAI Conference on Artificial Intelligence, AAAI 2021 . 4232–4240
Xin Lin, Zhenya Huang, Hongke Zhao, Enhong Chen, Qi Liu, Hao Wang, and Shijin Wang. 2021 · 2021
Later among the works it cites.
Math Word Problem Solving with Explicit Numerical Values. In Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, ACL/IJCNLP 2021 . 5859–5869
Qinzhuo Wu, Qi Zhang, Zhongyu Wei, and Xuanjing Huang. 2021 · 2021
Later among the works it cites.