2026 Mo Yu: Computer Science Researcher – H-Index, Publications & Awards

Discipline name	D-Index	World Ranking	Current World Ranking	National Ranking	Current National Ranking	Publications	Citations
Computer Science	43	7837	7613	3390	3263	128	10602

Overview

Mo Yu is a researcher affiliated with IBM in the United States with a focus on computer science, particularly in artificial intelligence and related subfields. Their publication record spans a range of topics centered on machine learning, natural language processing, and human-computer interaction.

The scientist's recent papers include:

StoryBuddy: A Human-AI Collaborative Chatbot for Parent-Child Interactive Storytelling with Flexible Parental Involvement (2022) published in the CHI Conference on Human Factors in Computing Systems
On the Origin of Hallucinations in Conversational Models: Is it the Datasets or the Models? (2022) published in the Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
CASS (2021) published in Proceedings of the ACM on Human-Computer Interaction
Query and Extract: Refining Event Extraction as Type-oriented Binary Decoding (2022) published in Findings of the Association for Computational Linguistics: ACL 2022
Invariant Rationalization (2020) published in arXiv (Cornell University)

Mo Yu's frequent coauthors include:

Shiyu Chang
Xiangyang Mou
Xiaoxiao Guo
Dakuo Wang
Saloni Potdar

The main publication venues where Mo Yu's work appears frequently are:

arXiv (Cornell University)
Transactions of the Association for Computational Linguistics
Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
Proceedings of the ACM on Human-Computer Interaction
Proceedings of the AAAI Conference on Artificial Intelligence

The primary fields of study for Mo Yu encompass computer science with a significant emphasis on artificial intelligence. Subfields receiving focused attention include:

Artificial Intelligence
Computer Vision and Pattern Recognition
Information Systems
Management Science and Operations Research
Molecular Biology

Their main research topics cover a diverse set of areas, including:

Topic Modeling
Natural Language Processing Techniques
Multimodal Machine Learning Applications
Domain Adaptation and Few-Shot Learning
AI in Service Interactions
Expert finding and Q&A systems
Advanced Graph Neural Networks

Best Publications

A Structured Self-Attentive Sentence Embedding.

Zhouhan Lin;Minwei Feng;Cicero Nogueira dos Santos;Mo Yu

1841
Citations
Target-dependent Twitter Sentiment Classification

Long Jiang;Mo Yu;Ming Zhou;Xiaohua Liu

1240
Citations
Comparative Study of CNN and RNN for Natural Language Processing

Wenpeng Yin;Katharina Kann;Mo Yu;Hinrich Schütze

1025
Citations
Improving Lexical Embeddings with Semantic Knowledge

Mo Yu;Mark Dredze

362
Citations
Improved Neural Relation Detection for Knowledge Base Question Answering

Mo Yu;Wenpeng Yin;Kazi Saidul Hasan;Cícero Nogueira dos Santos

341
Citations
R 3 : Reinforced Ranker-Reader for Open-Domain Question Answering.

Shuohang Wang;Mo Yu;Xiaoxiao Guo;Zhiguo Wang

285
Citations
One-Shot Relational Learning for Knowledge Graphs

Wenhan Xiong;Mo Yu;Shiyu Chang;Xiaoxiao Guo

273
Citations
Differential Treatment for Stuff and Things: A Simple Unsupervised Domain Adaptation Method for Semantic Segmentation

Zhonghao Wang;Mo Yu;Yunchao Wei;Rogerio Feris

252
Citations
Diverse Few-Shot Text Classification with Multiple Metrics

Mo Yu;Xiaoxiao Guo;Jinfeng Yi;Shiyu Chang

248
Citations
Dilated Recurrent Neural Networks

Shiyu Chang;Yang Zhang;Wei Han;Mo Yu

244
Citations
Image Super-Resolution via Dual-State Recurrent Networks

Wei Han;Shiyu Chang;Ding Liu;Mo Yu

238
Citations
Cross-lingual Knowledge Graph Alignment via Graph Matching Neural Network

Kun Xu;Liwei Wang;Mo Yu;Yansong Feng

231
Citations
Improved Relation Extraction with Feature-Rich Compositional Embedding Models

Matthew R. Gormley;Mo Yu;Mark Dredze

188
Citations
DAG-GNN: DAG Structure Learning with Graph Neural Networks

Yue Yu;Jie Chen;Tian Gao;Mo Yu

168
Citations
Simple Question Answering by Attentive Convolutional Neural Network

Wenpeng Yin;Mo Yu;Bing Xiang;Bowen Zhou

166
Citations
Rethinking Cooperative Rationalization: Introspective Extraction and Complement Control

Mo Yu;Shiyu Chang;Yang Zhang;Tommi S. Jaakkola

163
Citations
Evidence Aggregation for Answer Re-Ranking in Open-Domain Question Answering

Shuohang Wang;Mo Yu;Jing Jiang;Wei Zhang

156
Citations
Improving Natural Language Inference Using External Knowledge in the Science Questions Domain

Xiaoyan Wang;Pavan Kapanipathi;Ryan Musa;Mo Yu

153
Citations
Improving Question Answering over Incomplete KBs with Knowledge-Aware Reader.

Wenhan Xiong;Mo Yu;Shiyu Chang;Xiaoxiao Guo

134
Citations
Leveraging Sentence-level Information with Encoder LSTM for Semantic Slot Filling

Gakuto Kurata;Bing Xiang;Bowen Zhou;Mo Yu

130
Citations
Sentence Embedding Alignment for Lifelong Relation Extraction.

Hong Wang;Wenhan Xiong;Mo Yu;Xiaoxiao Guo

123
Citations
Invariant Rationalization

Shiyu Chang;Yang Zhang;Mo Yu;Tommi Jaakkola

54
Citations

Frequent Co-Authors

Shiyu Chang University of California, Santa Barbara

William Yang Wang University of California, Santa Barbara

Bowen Zhou IBM (United States)

Tommi S. Jaakkola MIT

Bing Xiang Amazon (United States)

Gerald Tesauro IBM (United States)

Mark Dredze Johns Hopkins University

Kun Xu Beijing University of Posts and Telecommunications

Jing Jiang Singapore Management University

Yue Zhang Westlake University

External Links

Personal website of Mo Yu Google Scholar page

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