Takeshi Kojima

Artificial Intelligence · 2022

A researcher in the Science corpus: 1 paper; trusts 7 researchers and is trusted by 9 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 37 citations into it; #16,085 of 35,345 by trust here, #3,508 by citations
• Natural Language Processing — 17 citations into it
• Prompting & Reasoning — 17 citations into it; #117 of 359 by trust here, #93 by citations

Whom Takeshi Kojima trusts overall

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

1. K. McGrew
2. Alec Radford
3. Geoffrey E. Hinton
4. Timo Schick
5. Yoshua Bengio
6. Ilya Sutskever
7. Diederik P. Kingma
8. Laria Reynolds
9. Hannaneh Hajishirzi
10. Alex Krizhevsky

Who trusts Takeshi Kojima overall

1. Jie Huang
2. Kumar Shridhar
3. Jason Wei
4. Pan Lu
5. Wenhu Chen
6. Omar Khattab
7. Zhuosheng Zhang
8. Xinyun Chen
9. Satyapriya Krishna
10. Guohao Li

Papers from Takeshi Kojima's perspective

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

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

Their papers

• Large Language Models are Zero-Shot Reasoners (2022) — 7,591 citations