Zhikang Li

Computer Vision and Pattern Recognition · 2021–2022

A researcher in the Science corpus: 5 papers; trusts 415 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 207 citations into it
• Artificial Intelligence — 169 citations into it
• Multimodal Learning — 89 citations into it
• Generative Models — 68 citations into it
• Large Language Models — 57 citations into it
• Natural Language Processing — 55 citations into it
• Representation & Self-Supervised Learning — 28 citations into it
• Signal Processing — 6 citations into it

Whom Zhikang Li trusts overall

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

1. Geoffrey E. Hinton
2. Kaiming He
3. Diederik P. Kingma
4. Alex Krizhevsky
5. Yoshua Bengio
6. Ilya Sutskever
7. Yann LeCun
8. Ross B. Girshick
9. Oriol Vinyals
10. Jimmy Ba

Papers from Zhikang Li's perspective

Ordered by how strongly the researchers Zhikang 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. ImageNet classification with deep convolutional neural networks
3. Attention is All you Need (Neural Information Processing Systems)
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Long Short-Term Memory
6. ImageNet: A large-scale hierarchical image database
7. Gradient-based learning applied to document recognition
8. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• OFA: Unifying Architectures, Tasks, and Modalities Through a Simple Sequence-to-Sequence Learning Framework (2022) — 1,080 citations
• M6-UFC: Unifying Multi-Modal Controls for Conditional Image Synthesis via Non-Autoregressive Generative Transformers (2021) — 49 citations
• M6: A Chinese Multimodal Pretrainer (2021) — 152 citations
• Unifying Architectures, Tasks, and Modalities Through a Simple Sequence-to-Sequence Learning Framework (2022) — 252 citations
• UFC-BERT: Unifying Multi-Modal Controls for Conditional Image Synthesis (2021) — 43 citations