World's Best Scientists 2026 revealed!

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Computer Science

D-Index
33
Citations
6539
World Ranking
12474
National Ranking
482

Overview

Lili Mou is affiliated with the University of Waterloo in Canada and specializes in computer science, with a particular focus on artificial intelligence. Their scholarly work encompasses 109 publications primarily in the field of computer science, with 90 of those specifically in artificial intelligence. Other subfields of study include computer vision and pattern recognition, information systems, signal processing, and cognitive neuroscience.

The research topics covered by Lili Mou's publications span several areas:

  • Topic Modeling
  • Natural Language Processing Techniques
  • Advanced Text Analysis Techniques
  • Multimodal Machine Learning Applications
  • Machine Learning and Data Classification
  • Software Engineering Research
  • Music and Audio Processing

The scientist has contributed to numerous papers with various coauthors, frequently collaborating with:

  • Yanshuai Cao
  • Yuqiao Wen
  • Chenyang Huang
  • Behzad Shayegh
  • Osmar R. Zai͏̈ane

Lili Mou's research has been published in multiple venues, with a substantial number of papers appearing in:

  • arXiv (Cornell University)
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • Neurocomputing
  • Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
  • Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment

Selected recent papers illustrate the range and focus of their work:

  • TreeGen: A Tree-Based Transformer Architecture for Code Generation, 2020, Proceedings of the AAAI Conference on Artificial Intelligence
  • Unsupervised Text Generation by Learning from Search, 2020, arXiv (Cornell University)
  • Simulated annealing for optimization of graphs and sequences, 2021, Neurocomputing
  • Document-Level Relation Extraction with Sentences Importance Estimation and Focusing, 2022, Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
  • Non-Autoregressive Translation with Layer-Wise Prediction and Deep Supervision, 2021, arXiv (Cornell University)

Best Publications

  • Classifying Relations via Long Short Term Memory Networks along Shortest Dependency Paths

    Yan Xu;Lili Mou;Ge Li;Yunchuan Chen

  • Convolutional neural networks over tree structures for programming language processing

    Lili Mou;Ge Li;Lu Zhang;Tao Wang

  • Distilling Task-Specific Knowledge from BERT into Simple Neural Networks

    Raphael Tang;Yao Lu;Linqing Liu;Lili Mou

  • Natural Language Inference by Tree-Based Convolution and Heuristic Matching

    Lili Mou;Rui Men;Ge Li;Yan Xu

  • How Transferable are Neural Networks in NLP Applications

    Lili Mou;Zhao Meng;Rui Yan;Ge Li

  • Disentangled Representation Learning for Non-Parallel Text Style Transfer

    Vineet John;Lili Mou;Hareesh Bahuleyan;Olga Vechtomova

  • Improved Relation Classification by Deep Recurrent Neural Networks with Data Augmentation

    Yan Xu;Ran Jia;Lili Mou;Ge Li

  • Sequence to Backward and Forward Sequences: A Content-Introducing Approach to Generative Short-Text Conversation

    Lili Mou;Yiping Song;Rui Yan;Ge Li

  • RUBER: An Unsupervised Method for Automatic Evaluation of Open-Domain Dialog Systems

    Chongyang Tao;Lili Mou;Dongyan Zhao;Rui Yan

  • Affective Neural Response Generation

    Nabiha Asghar;Pascal Poupart;Jesse Hoey;Xin Jiang

  • TreeGen: A Tree-Based Transformer Architecture for Code Generation

    Zeyu Sun;Qihao Zhu;Yingfei Xiong;Yican Sun

  • CGMH: Constrained Sentence Generation by Metropolis-Hastings Sampling

    Ning Miao;Hao Zhou;Lili Mou;Rui Yan

  • Classifying Relations via Long Short Term Memory Networks along Shortest Dependency Path

    Xu Yan;Lili Mou;Ge Li;Yunchuan Chen

  • Building Program Vector Representations for Deep Learning

    Hao Peng;Lili Mou;Ge Li;Yuxuan Liu

  • Discriminative Neural Sentence Modeling by Tree-Based Convolution

    Lili Mou;Hao Peng;Ge Li;Yan Xu

  • How to Make Context More Useful? An Empirical Study on Context-Aware Neural Conversational Models

    Zhiliang Tian;Rui Yan;Lili Mou;Yiping Song

  • A Grammar-Based Structural CNN Decoder for Code Generation

    Zeyu Sun;Qihao Zhu;Lili Mou;Yingfei Xiong

  • Order-Planning Neural Text Generation From Structured Data

    Lei Sha;Lili Mou;Tianyu Liu;Pascal Poupart

  • Generating Sentences from Disentangled Syntactic and Semantic Spaces.

    Yu Bao;Hao Zhou;Shujian Huang;Lei Li

  • Building Program Vector Representations for Deep Learning

    Lili Mou;Ge Li;Yuxuan Liu;Hao Peng

  • TBCNN: A Tree-Based Convolutional Neural Network for Programming Language Processing.

    Lili Mou;Ge Li;Zhi Jin;Lu Zhang

Frequent Co-Authors

Lu Zhang
Lu Zhang Peking University
Rui Yan
Rui Yan Renmin University of China
Pascal Poupart
Pascal Poupart University of Waterloo
Zhengdong Lu
Zhengdong Lu Huawei Technologies (China)
Yingfei Xiong
Yingfei Xiong Peking University
Hang Li
Hang Li ByteDance
Dongyan Zhao
Dongyan Zhao Peking University
Tao Wang
Tao Wang Stanford University
Frank Keller
Frank Keller University of Edinburgh
Yu Wu
Yu Wu Microsoft Research Asia (China)

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