Zifan Li

Natural Language Processing · 2018–2019

A researcher in the Science corpus: 4 papers; trusts 44 researchers and is trusted by 20 researchers here, as inferred from the citation graph.

Subfields

• Natural Language Processing — 103 citations into it; #1,816 of 5,688 by trust here, #1,221 by citations
• Artificial Intelligence — 102 citations into it; #8,643 of 35,345 by trust here, #4,393 by citations
• Information Systems — 28 citations into it; #4,034 of 8,771 by trust here, #541 by citations
• Computer Vision and Pattern Recognition — 24 citations into it
• Management Science and Operations Research — 11 citations into it
• Model Architectures — 8 citations into it
• Reinforcement Learning — 8 citations into it
• Signal Processing — 5 citations into it

Whom Zifan Li trusts overall

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

1. Diederik P. Kingma
2. John Wieting
3. Geoffrey E. Hinton
4. Oriol Vinyals
5. Richard Socher
6. Ilya Sutskever
7. Yoshua Bengio
8. Jimmy Ba
9. Jeffrey Pennington
10. Alex Krizhevsky

Who trusts Zifan Li overall

1. Tao Yu
2. Rui Zhang
3. Michihiro Yasunaga
4. Haoyang Li
5. Ziyu Yao
6. Kevin Lin
7. Ben Bogin
8. Jiaqi Guo
9. Pengcheng He
10. Byeong-Hoon So

Papers from Zifan Li's perspective

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

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

Their papers

• Spider: A Large-Scale Human-Labeled Dataset for Complex and Cross-Domain Semantic Parsing and Text-to-SQL Task (2018) — 1,963 citations
• TypeSQL: Knowledge-Based Type-Aware Neural Text-to-SQL Generation (2018) — 308 citations
• CoSQL: A Conversational Text-to-SQL Challenge Towards Cross-Domain Natural Language Interfaces to Databases (2019) — 312 citations
• SyntaxSQLNet: Syntax Tree Networks for Complex and Cross-Domain Text-to-SQL Task (2018) — 229 citations