Ming-li Wu

Artificial Intelligence · 2022

A researcher in the Science corpus: 1 paper; trusts 25 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 30 citations into it
• Natural Language Processing — 20 citations into it
• Large Language Models — 15 citations into it
• Computer Vision and Pattern Recognition — 12 citations into it
• Prompting & Reasoning — 8 citations into it

Whom Ming-li Wu trusts overall

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

1. Alec Radford
2. Timo Schick
3. Geoffrey E. Hinton
4. Yann LeCun
5. Yoshua Bengio
6. Diederik P. Kingma
7. Ilya Sutskever
8. Jacob Devlin
9. Alex Krizhevsky

Papers from Ming-li Wu's perspective

Ordered by how strongly the researchers Ming-li Wu trusts endorse each paper. Same corpus, a different order for every researcher.

1. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
2. Attention is All you Need (Neural Information Processing Systems)
3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
4. ImageNet classification with deep convolutional neural networks
5. Long Short-Term Memory
6. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
7. Language Models are Unsupervised Multitask Learners
8. ImageNet: A large-scale hierarchical image database
9. Gradient-based learning applied to document recognition
10. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)

Their papers

• Pre-trained Language Models Can be Fully Zero-Shot Learners (2022) — 42 citations