Deyao Zhu

Artificial Intelligence · 2023

A researcher in the Science corpus: 2 papers; trusts 98 researchers and is trusted by 5 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 80 citations into it; #21,857 of 35,345 by trust here, #4,526 by citations
• Computer Vision and Pattern Recognition — 72 citations into it; #13,405 of 21,575 by trust here, #3,445 by citations
• Multimodal Learning — 48 citations into it; #872 of 1,211 by trust here, #343 by citations
• Evaluation & Benchmarks — 11 citations into it
• Natural Language Processing — 10 citations into it

Whom Deyao Zhu trusts overall

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

1. Geoffrey E. Hinton
2. Kaiming He
3. Alex Krizhevsky
4. Yoshua Bengio
5. Diederik P. Kingma
6. Ilya Sutskever
7. Yann LeCun
8. Ross B. Girshick
9. Vicente Ordonez
10. Alec Radford

Who trusts Deyao Zhu overall

1. Renrui Zhang
2. Lin Chen
3. Kunchang Li
4. Jinze Bai
5. Hang Zhang
6. Penghao Wu
7. Muhammad Maaz
8. Peng Gao
9. Wei Zhang
10. Hanoona Abdul Rasheed

Papers from Deyao Zhu's perspective

Ordered by how strongly the researchers Deyao Zhu 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. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
8. Gradient-based learning applied to document recognition
9. ImageNet Large Scale Visual Recognition Challenge
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• MiniGPT-4: Enhancing Vision-Language Understanding with Advanced Large Language Models (2023) — 3,250 citations
• MiniGPT-v2: large language model as a unified interface for vision-language multi-task learning (2023) — 726 citations