Zhongyang Li

Artificial Intelligence · 2018–2020

A researcher in the Science corpus: 4 papers; trusts 137 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 71 citations into it; #27,160 of 35,345 by trust here, #22,463 by citations
• Natural Language Processing — 69 citations into it; #4,004 of 5,688 by trust here, #3,977 by citations
• Computer Vision and Pattern Recognition — 28 citations into it
• Representation & Self-Supervised Learning — 12 citations into it
• Graph Learning — 7 citations into it
• Model Architectures — 7 citations into it
• Large Language Models — 6 citations into it

Whom Zhongyang Li trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Yoshua Bengio
2. Ilya Sutskever
3. Dzmitry Bahdanau
4. Geoffrey E. Hinton
5. Kyunghyun Cho
6. Diederik P. Kingma
7. Tomas Mikolov
8. Alex Krizhevsky
9. Alec Radford
10. Yann LeCun

Who trusts Zhongyang Li overall

1. Xiao Ding
2. Nathaniel Weir
3. Pei Ke
4. Xipeng Qiu
5. Shu Wu
6. Ting-Wei Liu
7. Fuli Luo
8. Shirui Pan
9. Peter West
10. Ben Zhou

Papers from Zhongyang Li's perspective

Ordered by how strongly the researchers Zhongyang Li trusts endorse each paper. Same corpus, a different order for every researcher.

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet classification with deep convolutional neural networks
3. Long Short-Term Memory
4. Attention is All you Need (Neural Information Processing Systems)
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
9. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
10. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)

Their papers

• Constructing Narrative Event Evolutionary Graph for Script Event Prediction (2018) — 218 citations
• Guided Generation of Cause and Effect (2020) — 89 citations
• Story Ending Prediction by Transferable BERT (2019) — 54 citations
• Generating Reasonable and Diversified Story Ending Using Sequence to Sequence Model with Adversarial Training (2018) — 42 citations