Kristy Lee

Artificial Intelligence · 2021

A researcher in the Science corpus: 2 papers; trusts 54 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 83 citations into it; #26,404 of 35,345 by trust here, #15,542 by citations
• Natural Language Processing — 56 citations into it
• Evaluation & Benchmarks — 27 citations into it
• Large Language Models — 20 citations into it
• Computer Vision and Pattern Recognition — 14 citations into it
• Prompting & Reasoning — 13 citations into it; #200 of 359 by trust here, #225 by citations

Whom Kristy Lee trusts overall

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

1. Geoffrey E. Hinton
2. Yann LeCun
3. Yoshua Bengio
4. Diederik P. Kingma
5. Jacob Devlin
6. Richard Socher
7. Alex Krizhevsky
8. Ilya Sutskever
9. Timo Schick
10. Junbo Jake Zhao

Who trusts Kristy Lee overall

1. Daniel Khashabi
2. Swaroop Mishra
3. Sewon Min
4. Tim Dettmers
5. Alexander Wan
6. Jonathan Bragg
7. Yanda Chen

Papers from Kristy Lee's perspective

Ordered by how strongly the researchers Kristy Lee 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Long Short-Term Memory
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. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
10. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)

Their papers

• Adapting Language Models for Zero-shot Learning by Meta-tuning on Dataset and Prompt Collections (2021) — 188 citations
• Meta-tuning Language Models to Answer Prompts Better (2021) — 13 citations