Jinhyuk Lee

Artificial Intelligence · with Kang · 2018–2021

A researcher in the Science corpus: 10 papers; trusts 518 researchers and is trusted by 42 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 247 citations into it; #5,843 of 35,345 by trust here, #3,023 by citations
• Natural Language Processing — 194 citations into it; #1,299 of 5,688 by trust here, #730 by citations
• Computer Vision and Pattern Recognition — 122 citations into it; #12,161 of 21,575 by trust here, #8,021 by citations
• Information Retrieval & Search — 99 citations into it; #286 of 1,022 by trust here, #235 by citations
• Evaluation & Benchmarks — 41 citations into it
• Representation & Self-Supervised Learning — 26 citations into it; #3,035 of 3,145 by trust here, #2,454 by citations
• Molecular Biology — 22 citations into it; #4,779 of 17,773 by trust here, #2,983 by citations
• Information Systems — 20 citations into it; #8,525 of 8,771 by trust here, #3,640 by citations

Whom Jinhyuk Lee trusts overall

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

1. Geoffrey E. Hinton
2. Diederik P. Kingma
3. Minjoon Seo
4. Yoshua Bengio
5. Danqi Chen
6. Kenton C. T. Lee
7. Ilya Sutskever
8. Kaiming He
9. Alex Krizhevsky
10. Jacob Devlin

Who trusts Jinhyuk Lee overall

1. Robin Jia
2. Danqi Chen
3. M. V. Koroteev
4. Xiaochuang Han
5. Iz Beltagy
6. Wayne Xin Zhao
7. Michihiro Yasunaga
8. Gautier Izacard
9. Minjoon Seo
10. Michael Lewis

Papers from Jinhyuk Lee's perspective

Ordered by how strongly the researchers Jinhyuk Lee 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
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. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
8. Gradient-based learning applied to document recognition
9. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
10. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)

Their papers

• BioBERT: a pre-trained biomedical language representation model for biomedical text mining (2019) — 7,641 citations
• Real-Time Open-Domain Question Answering with Dense-Sparse Phrase Index (2019) — 165 citations
• Ranking Paragraphs for Improving Answer Recall in Open-Domain Question Answering (2018) — 90 citations
• Learning Dense Representations of Phrases at Scale (2020) — 130 citations
• Simple Entity-Centric Questions Challenge Dense Retrievers (2021) — 213 citations
• Look at the First Sentence: Position Bias in Question Answering (2020) — 123 citations
• CollaboNet: collaboration of deep neural networks for biomedical named entity recognition (2018) — 147 citations
• Phrase Retrieval Learns Passage Retrieval, Too (2021) — 50 citations
• Contextualized Sparse Representation with Rectified N-Gram Attention for Open-Domain Question Answering (2019) — 53 citations
• Contextualized Sparse Representations for Real-Time Open-Domain Question Answering (2019) — 31 citations