Long Lian

Computer Vision and Pattern Recognition · with Wang · 2023–2025

A researcher in the Science corpus: 2 papers; trusts 8 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 54 citations into it
• Generative Models — 30 citations into it

Whom Long Lian trusts overall

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

1. Alex Krizhevsky
2. Diederik P. Kingma
3. Geoffrey E. Hinton
4. Yoshua Bengio
5. Kaiming He
6. Alex Nichol
7. Jonathan Ho
8. Prafulla Dhariwal
9. Yann LeCun
10. Tim Salimans

Papers from Long Lian's perspective

Ordered by how strongly the researchers Long Lian 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. Learning Multiple Layers of Features from Tiny Images
4. Attention is All you Need (Neural Information Processing Systems)
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. ImageNet: A large-scale hierarchical image database
7. Gradient-based learning applied to document recognition
8. Long Short-Term Memory
9. GENERATIVE ADVERSARIAL NETS
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• A benchmark of expert-level academic questions to assess AI capabilities (2025) — 349 citations
• Q-Diffusion: Quantizing Diffusion Models (2023) — 316 citations