Shen-Yun Miao

Artificial Intelligence · 2020

A researcher in the Science corpus: 1 paper; trusts 7 researchers and is trusted by 6 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 18 citations into it; #21,616 of 35,345 by trust here, #13,353 by citations
• Natural Language Processing — 18 citations into it; #3,687 of 5,688 by trust here, #2,846 by citations
• Evaluation & Benchmarks — 5 citations into it; #1,956 of 3,147 by trust here, #1,740 by citations
• Information Systems — 5 citations into it; #4,638 of 8,771 by trust here, #2,203 by citations

Whom Shen-Yun Miao trusts overall

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

1. Subhro Roy
2. Steven Bird
3. Dan Roth
4. Peter Clark
5. Christopher D. Manning
6. Oren Etzioni
7. Aida Amini
8. Yefim Bakman
9. Salim Roukos
10. Shuming Shi

Who trusts Shen-Yun Miao overall

1. Kumar Shridhar
2. Arkil Patel
3. Yifei Li
4. Xuezhi Wang
5. Jiaqi Chen
6. Timo Schick
7. Yihuai Lan
8. Cheng-Yu Hsieh
9. Karl Cobbe
10. Daya Guo

Papers from Shen-Yun Miao's perspective

Ordered by how strongly the researchers Shen-Yun Miao trusts endorse each paper. Same corpus, a different order for every researcher.

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

Their papers

• A Diverse Corpus for Evaluating and Developing English Math Word Problem Solvers (2020) — 482 citations