Yuwei Wu
Natural Language Processing · with Zhou · 2018–2019
A researcher in the Science corpus: 4 papers; trusts 76 researchers and is trusted by 3 researchers here, as inferred from the citation graph.
Subfields
- Natural Language Processing — 136 citations into it; #3,891 of 5,688 by trust here, #2,660 by citations
- Artificial Intelligence — 129 citations into it; #23,183 of 35,345 by trust here, #12,387 by citations
- Evaluation & Benchmarks — 34 citations into it
- Large Language Models — 12 citations into it
- Model Architectures — 12 citations into it
Whom Yuwei Wu trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Yoshua Bengio
- Diederik P. Kingma
- Alec Radford
- Richard Socher
- Ilya Sutskever
- Alex Krizhevsky
- Jacob Devlin
- Zhuosheng Zhang
- Christopher D. Manning
Who trusts Yuwei Wu overall
- Zhuosheng Zhang
- Junjie Yang
- Ondrej Dusek
- Ben Burtenshaw
- Yiming Cui
- Hai Zhao
- Shuailiang Zhang
- Yu-An Chung
Papers from Yuwei Wu's perspective
Ordered by how strongly the researchers Yuwei Wu trusts endorse each paper. Same corpus, a different order for every researcher.
- Attention is All you Need (Neural Information Processing Systems)
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Long Short-Term Memory
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- ImageNet classification with deep convolutional neural networks
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
- ImageNet: A large-scale hierarchical image database
- Gradient-based learning applied to document recognition
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
Their papers
- Dual Co-Matching Network for Multi-choice Reading Comprehension (2019) — 138 citations
- Semantics-aware BERT for Language Understanding (2019) — 401 citations
- SG-Net: Syntax-Guided Machine Reading Comprehension (2019) — 195 citations
- I Know What You Want: Semantic Learning for Text Comprehension (2018) — 21 citations