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Mo Yu

Research Staff Member
IBM Research AI

E-mail: yum AT us DOT ibm DOT com


Full Publication List

Pre-Prints

  • L. Song, Z. Wang, M. Yu, Y. Zhang, R. Florian, D. Gildea. ``Exploring graph-structured passage representation for multi-hop reading comprehension with graph neural networks''. ArXiv 2018. 
  • M. Yu*, X. Guo*, J. Yi*, S. Chang, S. Potdar, G. Tesauro, H. Wang, B. Zhou. ``Diverse Few-Shot Text Classification with Multiple Metrics''. ArXiv 2017. 
  • W. Yin, K. Kann, M. Yu, H. Schütze. ``Comparative study of cnn and rnn for natural language processing''. ArXiv 2017. 
  • Y. Yu, W. Zhang, K. Hasan, M. Yu, B. Xiang, B. Zhou. ``End-to-end answer chunk extraction and ranking for reading comprehension''. ArXiv 2016. 

2019

  • H. Wang, W. Xiong, M. Yu, X. Guo, S. Chang, WY. Wang. ``Sentence Embedding Alignment for Lifelong Relation Extraction''. NAACL 2019. 
  • W. Xiong, J. Wu, D. Lei, M. Yu, S. Chang, X. Guo, WY. Wang. ``Imposing Label-Relational Inductive Bias for Extremely Fine-Grained Entity Typing''. NAACL 2019. 
  • X. Guo, S. Chang, M. Yu, G. Tesauro, M. Campbell. ``Hybrid Reinforcement Learning with Expert State Sequences''. AAAI 2019. 
  • X. Wang, P. Kapanipathi, R. Musa, M. Yu, K. Talamadupula, I. Abdelaziz, M. Chang, A. Fokoue, B. Makni, N. Mattei, M. Witbrock. ``Improving Natural Language Inference Using External Knowledge in the Science Questions Domain''. AAAI 2019. 
  • Y. Yu, J. Chen, T. Gao, M. Yu. ``DAG-GNN: DAG Structure Learning with Graph Neural Networks''. ICML 2019. 
  • H. Wang*, M. Tan*, M. Yu*, S. Chang, D. Wang, K. Xu, X. Guo and S. Potdar. ``Extracting Multiple-Relations in One-Pass with Pre-Trained Transformers''. ACL 2019. 
  • W. Xiong, M. Yu, S. Chang, X. Guo and WY. Wang. ``Improving Question Answering over Incomplete KBs with Knowledge-Aware Reader''. ACL 2019. 
  • Kun Xu, Liwei Wang, Mo Yu, Yansong Feng, Yan Song, Zhiguo Wang and Dong Yu. ``Cross-lingual Knowledge Graph Alignment via Graph Matching Neural Network''. ACL 2019. 

2018

  • M. Yu*, X. Guo*, J. Yi*, S. Chang, S. Potdar, Y. Cheng, G. Tesauro, H. Wang, B. Zhou. ``Diverse Few-Shot Text Classification with Multiple Metrics''. NAACL 2018. 
  • S. Wang*, M. Yu*, T. Klinger, W. Zhang, X. Guo, S. Chang, Z. Wang, J. Jiang, G. Tesauro, M. Campbell . ``Evidence Aggregation for Answer Re-Ranking in Open-Domain Question Answering''. ICLR 2018. 
  • S. Wang, M. Yu, X. Guo, Z. Wang, T. Klinger, W. Zhang, S. Chang, G. Tesauro, B. Zhou. ``R$^ 3$: Reinforced Reader-Ranker for Open-Domain Question Answering''. AAAI 2018. 
  • S. Wang, M. Yu, S. Chang, J. Jiang. ``A Co-Matching Model for Multi-choice Reading Comprehension''. ACL 2018. 
  • W. Xiong, X. Guo, M. Yu, S. Chang, WY. Wang. ``Scheduled Policy Optimization for Natural Language Communication with Intelligent Agents''. IJCAI 2018. 
  • W. Han, S. Chang, D. Liu, M. Yu, M. Witbrock, TS. Huang. ``Image Super-Resolution via Dual-State Recurrent Networks''. CVPR 2018. 
  • W. Xiong, M. Yu, S. Chang, X. Guo, WY. Wang. ``One-Shot Relational Learning for Knowledge Graphs''. EMNLP 2018. 
  • Y. Bao, S. Chang, M. Yu, R. Barzilay. ``Deriving Machine Attention from Human Rationales''. EMNLP 2018. 
  • K. Xu, L. Wu, Z. Wang, M. Yu, L. Chen, V. Sheinin. ``Exploiting Rich Syntactic Information for Semantic Parsing with Graph-to-Sequence Model''. EMNLP 2018. 
  • T. Guo, S. Chang, M. Yu, K. Bai. ``Improving Reinforcement Learning Based Image Captioning with Natural Language Prior''. EMNLP 2018. 

2017

  • M. Yu, W. Yin, K. Hasan, C. dos Santos, B. Xiang, B. Zhou. ``Improved Neural Relation Detection for Knowledge Base Question Answering''. ACL 2017. 
  • Z. Lin, M. Feng, CN. Santos, M. Yu, B. Xiang, B. Zhou, Y. Bengio. ``A structured self-attentive sentence embedding''. ICLR 2017. 
  • S. Chang, Y. Zhang, W. Han, M. Yu, X. Guo, W. Tan, X. Cui, M. Witbrock, M. Hasegawa-Johnson, TS. Huang. ``Dilated recurrent neural networks''. NIPS 2017. 
  • Y. Cheng, M. Yu, X. Guo, B. Zhou. ``Few-Shot Learning with Meta Metric Learners''. NIPS 2017 Workshop on Meta-Learning. 

2016

  • M. Yu, M. Dredze, R. Arora, M. Gormley. ``Embedding Lexical Features via Low-rank Tensors''. NAACL 2016. 
  • W. Yin, M. Yu, B. Xiang, B. Zhou, H. Schütze. ``Simple question answering by attentive convolutional neural network''. COLING 2016.
  • G. Kurata, B. Xiang, B. Zhou, M. Yu. ``Leveraging sentencelevel information with encoder LSTM for natural language understanding''. EMNLP 2016.

2015

  • M. Yu, M. Dredze. ``Learning Composition Models for Phrase Embeddings''. TACL, 2015.
  • M. Yu, M. Gormley, M. Dredze. ``Combining Word Embeddings and Feature Embeddings for Fine-grained Relation Extraction''.  NAACL 2015.
  • M. Gormley*, M. Yu*, M. Dredze. ``Improved Relation Extraction with Feature-rich Compositional Embedding Models''. EMNLP, 2015.
  • N. Peng, M. Yu, M. Dredze. ``An empirical study of chinese name matching and applications''. ACL, 2015.
  • N. Peng, F. Ferraro, M. Yu, N. Andrews, J. DeYoung, M. Thomas. M. Gormley, T. Wolfe, C. Harman, B. Van Durme, M. Dredze``A Concrete Chinese NLP Pipeline''. NAACL, 2015.

2014

  • T. Zhao*, M. Yu*, Y. Wang, R. Arora, H. Liu. ``Accelerated Mini-batch Randomized Block Coordinate Descent Method''. NIPS 2014.
  • M. Yu, M. Dredze. ``Improving Lexical Embeddings with Semantic Knowledge''. ACL 2014.
  • M. Yu, M. Gormley, M. Dredze. ``Improving Lexical Embeddings with Semantic Knowledge''. NIPS 2014 Workshop on Learning Semantics.

2013

  • M. Yu, T. Zhao and Y. Bai, H. Tian, D. Yu. ``Cross-lingual Projections between Languages from different Families''. ACL 2013.
  • M. Yu, T. Zhao, D. Dong, H. Tian, D. Yu. ``Compound Embedding Features for Semi-supervised Learning''. NAACL 2013.
  • M. Yu, T. Zhao, Y. Bai. ``Learning Domain Differences Automatically for Dependency Parsing Adaptation''. IJCAI, 2013.
  • M. Yu, T. Zhao, P. Hu. ``A Theoretical Analysis on Structured Learning with Noisy Data and its Applications''. Journal of Software 2013 (In Chinese).

Earlier Works

  • L. Jiang, M. Yu, M. Zhou, X. Liu, T. Zhao. Target-dependent Twitter Sentiment Classification. ACL 2011.
  • L. Liu, H. Cao, T. Watanabe, T. Zhao, M. Yu, C. Zhu. Locally Training the Log-Linear Model for SMT. EMNLP-CoNLL 2012.
  • Y. Ren, M. Yu, X. Wang, L. Zhang, W. Ma, Diversifying Landmark Image Search Results by Learning Interested Views from Community Photos. WWW2010 Proceedings
  • M. Yu, S. Wang, C. Zhu, T. Zhao: Semi-supervised learning for word sense disambiguation using parallel corpora. FSKD 2011: 1490-1494
  • P. Hu, M. Yu, J. Li, C. Zhu, T. Zhao: Semi-supervised Learning Framework for Cross-Lingual Projection. Web Intelligence/IAT Workshops 2011: 213-216
  • H. Liang, L. Liu, M. Yu, Y. Liu, P. Hu, T. Li, C. Zhang, H. Cao, T. Zhao. Technique reports of HIT-Machine Intelligence & Translation Lab for CWMT2011 (In Chinese)
  • Z. Li, H. Li, M. Yu, T. Zhao, S. Li: Event Entailment Extraction Based on EM Iteration. IALP 2010: 101-104
  • X. Han, M. Yu, C. Zhu, and T. Zhao. A Sequence Kernel Method for Chinese Subcategorization Analysis. Chinese Journal of Electronics. Vol.19, No.3, July 2010.
  • X. Wang, M. Yu, L. Zhang, W. Ma, Argo: Intelligent Advertising Made Possible from Users’ Photos (demo paper). ACM MM09 Proceedings.
  • X. Wang, M. Yu, L. Zhang, W. Ma. Advertising based on users’ photos. IEEE ICME 2009 workshop.
  • X. Wang, M. Yu, L. Zhang, R. Cai, W. Ma. Argo: Intelligent Advertising by Mining a User’s Interest from His Photo Collections. ADKDD’09, June 28, 2009
  • C. Zhu, M. Yu, T. Zhao. Chinese Word Segmenter Based on Discriminative Classifiers Integration. Journal of Computational Information Systems3:5(2008) 1-7