David Errington

Artificial Intelligence · 2021

A researcher in the Science corpus: 1 paper; trusts 3 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 23 citations into it
• Natural Language Processing — 16 citations into it
• Safety, Robustness & Interpretability — 16 citations into it

Whom David Errington trusts overall

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

1. Jieyu Zhao
2. Kenton C. T. Lee
3. Geoffrey E. Hinton

Papers from David Errington's perspective

Ordered by how strongly the researchers David Errington 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. Long Short-Term Memory
5. ImageNet classification with deep convolutional neural networks
6. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
7. Distilling the Knowledge in a Neural Network (arXiv.org)
8. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
9. RoBERTa: A Robustly Optimized BERT Pretraining Approach (arXiv.org)
10. ImageNet: A large-scale hierarchical image database

Their papers

• Stereotype and Skew: Quantifying Gender Bias in Pre-trained and Fine-tuned Language Models (2021) — 102 citations