Yusuke Oda

Natural Language Processing · 2015–2020

A researcher in the Science corpus: 8 papers; trusts 62 researchers and is trusted by 4 researchers here, as inferred from the citation graph.

Subfields

• Natural Language Processing — 122 citations into it; #4,021 of 5,688 by trust here, #2,203 by citations
• Artificial Intelligence — 119 citations into it; #23,071 of 35,345 by trust here, #5,924 by citations
• Computer Vision and Pattern Recognition — 40 citations into it
• Model Architectures — 32 citations into it
• Evaluation & Benchmarks — 29 citations into it; #2,956 of 3,147 by trust here, #2,482 by citations
• Large Language Models — 13 citations into it
• Optimization & Training — 10 citations into it
• Management Science and Operations Research — 7 citations into it

Whom Yusuke Oda trusts overall

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

1. Diederik P. Kingma
2. Ilya Sutskever
3. Yoshua Bengio
4. Philipp Koehn
5. Dzmitry Bahdanau
6. Geoffrey E. Hinton
7. Oriol Vinyals
8. Kyunghyun Cho
9. Jimmy Ba
10. Alex Krizhevsky

Who trusts Yusuke Oda overall

1. Pengcheng Yin
2. Xinyun Chen
3. Miltiadis Allamanis
4. Aditya Kanade
5. Graham Neubig
6. Raj Dabre
7. Benjamin Heinzerling
8. Li Dong
9. Bogdan Vasilescu
10. Alexander LeClair

Papers from Yusuke Oda's perspective

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

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

Their papers

• DyNet: The Dynamic Neural Network Toolkit (2017) — 391 citations
• Learning to Generate Pseudo-Code from Source Code Using Statistical Machine Translation (T) (2015) — 319 citations
• An Empirical Study of Mini-Batch Creation Strategies for Neural Machine Translation (2017) — 26 citations
• Findings of the Third Workshop on Neural Generation and Translation (2019) — 31 citations
• Findings of the Fourth Workshop on Neural Generation and Translation (2020) — 16 citations
• Overview of the 5th Workshop on Asian Translation (2019) — 46 citations
• Overview of the 4th Workshop on Asian Translation (2017) — 47 citations
• Neural Machine Translation via Binary Code Prediction (2017) — 17 citations