Philip G. Feldman

Large Language Models · 2022

A researcher in the Science corpus: 1 paper; trusts 5 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Large Language Models — 8 citations into it

Whom Philip G. Feldman trusts overall

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

1. Alec Radford
2. John Zimmerman
3. Mathieu Jacomy
4. Karthik Narasimhan
5. Jodi L. Forlizzi
6. Tommaso Venturini
7. Jacob Devlin
8. Luciano Floridi

Who trusts Philip G. Feldman overall

1. Irene Solaiman

Papers from Philip G. Feldman's perspective

Ordered by how strongly the researchers Philip G. Feldman 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. ImageNet classification with deep convolutional neural networks
4. Language Models are Unsupervised Multitask Learners
5. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
6. Language Models are Few-Shot Learners (Neural Information Processing Systems)
7. Long Short-Term Memory
8. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
9. Improving Language Understanding by Generative Pre-Training
10. Gradient-based learning applied to document recognition

Their papers

• Ethics, Rules of Engagement, and AI: Neural Narrative Mapping Using Large Transformer Language Models (2022)