Shun Kiyono

Artificial Intelligence · 2017–2021

A researcher in the Science corpus: 4 papers; trusts 69 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 89 citations into it
• Natural Language Processing — 64 citations into it
• Computer Vision and Pattern Recognition — 33 citations into it
• Model Architectures — 26 citations into it
• Evaluation & Benchmarks — 13 citations into it

Whom Shun Kiyono trusts overall

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

1. Diederik P. Kingma
2. Yoshua Bengio
3. Ilya Sutskever
4. Geoffrey E. Hinton
5. Dzmitry Bahdanau
6. Rico Sennrich
7. Sepp Hochreiter
8. Alex Graves
9. Alex Krizhevsky
10. Oriol Vinyals

Who trusts Shun Kiyono overall

1. Rui Zhang
2. Ofir Press
3. Sho Takase
4. Renjie Zheng
5. Joel R. Tetreault
6. Noah A. Smith
7. Changhan Wang
8. Jun Suzuki
9. Amirhossein Kazemnejad

Papers from Shun Kiyono's perspective

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

Their papers

• SHAPE: Shifted Absolute Position Embedding for Transformers (2021) — 60 citations
• Encoder-Decoder Models Can Benefit from Pre-trained Masked Language Models in Grammatical Error Correction (2020) — 163 citations
• ESPnet-ST: All-in-One Speech Translation Toolkit (2020) — 174 citations
• Source-side Prediction for Neural Headline Generation (2017) — 9 citations