Edward Cui

Artificial Intelligence · 2020–2021

A researcher in the Science corpus: 5 papers; trusts 191 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 123 citations into it
• Computer Vision and Pattern Recognition — 114 citations into it
• Multimodal Learning — 75 citations into it
• Natural Language Processing — 70 citations into it
• Large Language Models — 33 citations into it
• Evaluation & Benchmarks — 24 citations into it
• Optimization & Training — 6 citations into it
• General Social Sciences — 5 citations into it

Whom Edward Cui trusts overall

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

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

Papers from Edward Cui's perspective

Ordered by how strongly the researchers Edward Cui 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. Going deeper with convolutions
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• ImageBERT: Cross-modal Pre-training with Large-scale Weak-supervised Image-Text Data (2020) — 280 citations
• M3P: Learning Universal Representations via Multitask Multilingual Multimodal Pre-training (2021) — 120 citations
• XGLUE: A New Benchmark Datasetfor Cross-lingual Pre-training, Understanding and Generation (2020) — 398 citations
• XGPT: Cross-modal Generative Pre-Training for Image Captioning (2020) — 84 citations
• M3P: Learning Universal Representations via Multitask Multilingual Multimodal Pre-training (2020) — 7 citations