Kai Li

Artificial Intelligence · with Gupta · 2021–2023

A researcher in the Science corpus: 2 papers; trusts 13 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 46 citations into it
• Computer Vision and Pattern Recognition — 11 citations into it
• Optimization & Training — 7 citations into it
• Privacy & Security — 7 citations into it

Whom Kai Li trusts overall

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

1. Diederik P. Kingma
2. Kaiming He
3. Geoffrey E. Hinton
4. Alex Krizhevsky
5. Sergey Ioffe
6. Yoshua Bengio
7. Li Deng
8. Christian Szegedy
9. Yann LeCun
10. Jimmy Ba

Papers from Kai Li's perspective

Ordered by how strongly the researchers Kai Li 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. ImageNet classification with deep convolutional neural networks
4. ImageNet: A large-scale hierarchical image database
5. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
6. Gradient-based learning applied to document recognition
7. Attention is All you Need (Neural Information Processing Systems)
8. Long Short-Term Memory
9. Learning Multiple Layers of Features from Tiny Images
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Catastrophic Jailbreak of Open-source LLMs via Exploiting Generation (2023) — 525 citations
• Evaluating Gradient Inversion Attacks and Defenses in Federated Learning (2021) — 391 citations