Robert L Logan IV

Artificial Intelligence · 2020–2022

A researcher in the Science corpus: 4 papers; trusts 85 researchers and is trusted by 5 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 104 citations into it; #21,463 of 35,345 by trust here, #7,010 by citations
• Natural Language Processing — 60 citations into it
• Large Language Models — 43 citations into it; #662 of 799 by trust here, #478 by citations
• Computer Vision and Pattern Recognition — 32 citations into it
• Evaluation & Benchmarks — 27 citations into it
• Prompting & Reasoning — 19 citations into it; #184 of 359 by trust here, #162 by citations
• Representation & Self-Supervised Learning — 5 citations into it

Whom Robert L Logan IV trusts overall

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

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

Who trusts Robert L Logan IV overall

1. Timo Schick
2. Sewon Min
3. Abhilasha Ravichander
4. Banghao Chen
5. Sen Yang
6. Ning Ding
7. Joel Jang
8. Hinrich Schütze
9. Sang Michael Xie
10. Alex Troy Mallen

Papers from Robert L Logan IV's perspective

Ordered by how strongly the researchers Robert L Logan IV 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. ImageNet classification with deep convolutional neural networks
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. 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

• Impact of Pretraining Term Frequencies on Few-Shot Reasoning (2022) — 185 citations
• Eliciting Knowledge from Language Models Using Automatically Generated Prompts (2020) — 559 citations
• Cutting Down on Prompts and Parameters: Simple Few-Shot Learning with Language Models (2021) — 245 citations
• FRUIT: Faithfully Reflecting Updated Information in Text (2021) — 46 citations