Ting Fang Tan

Large Language Models · 2023

A researcher in the Science corpus: 2 papers; trusts 1 researcher and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Large Language Models — 30 citations into it

Whom Ting Fang Tan trusts overall

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

1. Jacob Devlin
2. Iz Beltagy
3. Geoffrey E. Hinton
4. Antonia Creswell
5. Alec Radford

Papers from Ting Fang Tan's perspective

Ordered by how strongly the researchers Ting Fang Tan trusts endorse each paper. Same corpus, a different order for every researcher.

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

Their papers

• Large language models in health care: Development, applications, and challenges (2023) — 322 citations
• Large language models in medicine (2023) — 3,417 citations