Doo Soon Kim
Artificial Intelligence · 2018–2020
A researcher in the Science corpus: 3 papers; trusts 26 researchers and is trusted by 1 researcher here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 49 citations into it; #32,796 of 35,345 by trust here, #11,072 by citations
- Natural Language Processing — 46 citations into it; #5,274 of 5,688 by trust here, #2,440 by citations
- Computer Vision and Pattern Recognition — 19 citations into it
- Evaluation & Benchmarks — 11 citations into it
- Model Architectures — 6 citations into it
Whom Doo Soon Kim trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Chin-Yew Lin
- Ilya Sutskever
- Geoffrey E. Hinton
- Yoshua Bengio
- Alex Graves
- Oriol Vinyals
- Christopher D. Manning
- Diederik P. Kingma
- Dzmitry Bahdanau
- Alex Krizhevsky
Who trusts Doo Soon Kim overall
Papers from Doo Soon Kim's perspective
Ordered by how strongly the researchers Doo Soon Kim 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)
- ImageNet classification with deep convolutional neural networks
- Long Short-Term Memory
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
Their papers
- A Discourse-Aware Attention Model for Abstractive Summarization of Long Documents (2018) — 950 citations
- Understanding Points of Correspondence between Sentences for Abstractive Summarization (2020) — 29 citations
- TutorialVQA: Question Answering Dataset for Tutorial Videos (2019) — 36 citations