Chenze Shao
Artificial Intelligence · 2018–2026
A researcher in the Science corpus: 4 papers; trusts 209 researchers and is trusted by 1 researcher here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 71 citations into it; #34,485 of 35,345 by trust here, #27,551 by citations
- Computer Vision and Pattern Recognition — 52 citations into it; #20,973 of 21,575 by trust here, #17,757 by citations
- Natural Language Processing — 47 citations into it
- Model Architectures — 20 citations into it
- Optimization & Training — 10 citations into it
- Evaluation & Benchmarks — 7 citations into it
- Reinforcement Learning — 6 citations into it
Whom Chenze Shao trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Alex Krizhevsky
- Geoffrey E. Hinton
- Diederik P. Kingma
- Yoshua Bengio
- Ronald J. Williams
- Yann LeCun
- Ilya Sutskever
- Kaiming He
- Dzmitry Bahdanau
- Matthew D. Zeiler
Who trusts Chenze Shao overall
Papers from Chenze Shao's perspective
Ordered by how strongly the researchers Chenze Shao trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
- Learning Multiple Layers of Features from Tiny Images
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
Their papers
- Greedy Search with Probabilistic N-gram Matching for Neural Machine Translation (2018) — 29 citations
- Overcoming Catastrophic Forgetting beyond Continual Learning: Balanced Training for Neural Machine Translation (2022) — 44 citations
- DeepSeek-V4: Towards Highly Efficient Million-Token Context Intelligence (2026) — 347 citations
- Modeling Fluency and Faithfulness for Diverse Neural Machine Translation (2019) — 28 citations