Linjun Shou
Microsoft (United States)(US)Microsoft Research Asia (China)(CN)
Publications by Year
Research Areas
Topic Modeling, Natural Language Processing Techniques, Multimodal Machine Learning Applications, Domain Adaptation and Few-Shot Learning, Advanced Graph Neural Networks
Most-Cited Works
- → CodeBERT: A Pre-Trained Model for Programming and Natural Languages(2020)2,312 cited
- → CodeXGLUE: A Machine Learning Benchmark Dataset for Code Understanding and Generation(2021)415 cited
- → XGLUE: A New Benchmark Dataset for Cross-lingual Pre-training, Understanding and Generation(2020)232 cited
- → Graph-Based Reasoning over Heterogeneous External Knowledge for Commonsense Question Answering(2020)187 cited
- → Unicoder: A Universal Language Encoder by Pre-training with Multiple Cross-lingual Tasks(2019)167 cited
- → Reinforced Multi-Teacher Selection for Knowledge Distillation(2021)117 cited
- → Model Compression with Two-stage Multi-teacher Knowledge Distillation for Web Question Answering System(2020)92 cited
- → TaskMatrix.AI: Completing Tasks by Connecting Foundation Models with Millions of APIs(2023)85 cited