Kai Yi

Computer Vision and Pattern Recognition · 2018–2021

A researcher in the Science corpus: 2 papers; trusts 355 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 92 citations into it
• Artificial Intelligence — 64 citations into it
• Multimodal Learning — 43 citations into it
• Natural Language Processing — 37 citations into it
• Large Language Models — 15 citations into it
• Evaluation & Benchmarks — 12 citations into it
• Medical Imaging — 5 citations into it

Whom Kai Yi trusts overall

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

1. Alex Krizhevsky
2. Geoffrey E. Hinton
3. Yoshua Bengio
4. Kaiming He
5. Ilya Sutskever
6. Diederik P. Kingma
7. Sepp Hochreiter
8. Ross B. Girshick
9. Yann LeCun
10. Shaoqing Ren

Papers from Kai Yi's perspective

Ordered by how strongly the researchers Kai Yi 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. ImageNet classification with deep convolutional neural networks
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Attention is All you Need (Neural Information Processing Systems)
5. Long Short-Term Memory
6. ImageNet: A large-scale hierarchical image database
7. Gradient-based learning applied to document recognition
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. ImageNet Large Scale Visual Recognition Challenge
10. Going deeper with convolutions

Their papers

• VisualGPT: Data-efficient Adaptation of Pretrained Language Models for Image Captioning (2021) — 299 citations
• Knowledge-based Recurrent Attentive Neural Network for Traffic Sign Detection (2018) — 5 citations