Belinda Z. Li

Artificial Intelligence · 2020–2021

A researcher in the Science corpus: 4 papers; trusts 62 researchers and is trusted by 12 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 79 citations into it; #13,423 of 35,345 by trust here, #4,101 by citations
• Natural Language Processing — 64 citations into it; #4,683 of 5,688 by trust here, #3,235 by citations
• Large Language Models — 30 citations into it
• Computer Vision and Pattern Recognition — 29 citations into it
• Evaluation & Benchmarks — 19 citations into it

Whom Belinda Z. Li trusts overall

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

1. Geoffrey E. Hinton
2. Yoshua Bengio
3. Percy Liang
4. Diederik P. Kingma
5. Ilya Sutskever
6. Alex Krizhevsky
7. Tomas Mikolov
8. Yann LeCun
9. Kaiming He
10. Richard Socher

Who trusts Belinda Z. Li overall

1. Yi Tay
2. Jie Huang
3. Shuhao Cao
4. Tri Dao
5. Shuang Li
6. Markus Norman Rabe
7. Sachin Mehta
8. Andrew Jaegle
9. Kevin Chen-Chuan Chang
10. Murray Shanahan

Papers from Belinda Z. Li's perspective

Ordered by how strongly the researchers Belinda Z. Li trusts endorse each paper. Same corpus, a different order for every researcher.

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

Their papers

• Linformer: Self-Attention with Linear Complexity (2020) — 2,339 citations
• Implicit Representations of Meaning in Neural Language Models (2021) — 240 citations
• Language Models as Fact Checkers? (2020) — 86 citations
• Quantifying Adaptability in Pre-trained Language Models with 500 Tasks (2021) — 18 citations