Yanshuai Cao
Senior Research Team Lead
PhD Computer Science, University of Toronto
Yanshuai Cao is a senior research team lead at Borealis AI. Currently, his research spans natural language processing, generative models, and adversarial machine learning. He conceived the idea for project Turing by Borealis AI, a cross-domain natural language database interface, and led the research to enable it. His long-term research goal is to create machines that can learn to reason and adapt quickly from as little data as possible.
Yanshuai received his PhD in Computer Science from the Department of Computer Science at the University of Toronto, where he was advised by Professor David J. Fleet and Professor Aaron Hertzmann.
Research Areas
Natural Language Processing
Computer Vision
Publications
June 3, 2021
Code Generation from Natural Language with Less Prior Knowledge and More Monolingual Data
Association for Computational Linguistics (ACL), 2021
June 3, 2021
Optimizing Deeper Transformers on Small Datasets
Association for Computational Linguistics (ACL), 2021
June 3, 2021
TURING: an Accurate and Interpretable Multi-Hypothesis Cross-Domain Natural Language Database Interface
Association for Computational Linguistics (ACL), 2021
June 3, 2021
A Globally Normalized Neural Model for Semantic Parsing
Workshop at Association for Computational Linguistics (ACL), 2021
July 12, 2020
Evaluating Lossy Compression Rates of Deep Generative Models
International Conference on Machine Learning (ICML), 2020
July 12, 2020
On Variational Learning of Controllable Representations for Text without Supervision
International Conference on Machine Learning (ICML), 2020
June 3, 2020
Better Long-Range Dependency by Bootstrapping A Mutual Information Regularizer
International Conference on Artificial Intelligence and Statistics (AISTATS), 2020
July 28, 2019
A Cross-Domain Transferable Neural Coherence Model
Association for Computational Linguistics (ACL), 2019
Dec. 3, 2018
Few-Shot Self Reminder to Overcome Catastrophic Forgetting
Workshop on Continual Learning (NeurIPS), 2018
Dec. 3, 2018
Compositional Hard Negatives for Visual Semantic Embeddings via an Adversary
Workshop on ViGIL (NeurIPS), 2018
July 15, 2018
Adversarial Contrastive Estimation
Association for Computational Linguistics (ACL), 2018
April 30, 2018
Improving GAN Training via Binarized Representation Entropy (BRE) Regularization
International Conference on Learning Representations (ICLR), 2018
Aug. 6, 2017
Implicit Manifold Learning on Generative Adversarial Networks
Workshop on Implicit Models (ICML), 2017