Nathaniel Weir

Artificial Intelligence · 2020–2023

A researcher in the Science corpus: 5 papers; trusts 116 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 115 citations into it
• Natural Language Processing — 82 citations into it
• Computer Vision and Pattern Recognition — 41 citations into it
• Large Language Models — 26 citations into it
• Evaluation & Benchmarks — 24 citations into it
• Representation & Self-Supervised Learning — 7 citations into it
• Management Science and Operations Research — 6 citations into it
• Optimization & Training — 5 citations into it

Whom Nathaniel Weir trusts overall

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

1. Diederik P. Kingma
2. Matt Post
3. Geoffrey E. Hinton
4. Yoshua Bengio
5. Ilya Sutskever
6. Jimmy Ba
7. Alex Krizhevsky
8. Yann LeCun
9. Ashish Vaswani
10. Kaiming He

Who trusts Nathaniel Weir overall

1. Vered Shwartz

Papers from Nathaniel Weir's perspective

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

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. Attention is All you Need (Neural Information Processing Systems)
3. ImageNet classification with deep convolutional neural networks
4. Long Short-Term Memory
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
7. Gradient-based learning applied to document recognition
8. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
9. ImageNet: A large-scale hierarchical image database
10. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)

Their papers

• COD3S: Diverse Generation with Discrete Semantic Signatures (2020) — 15 citations
• InFillmore: Frame-Guided Language Generation with Bidirectional Context (2021) — 5 citations
• “According to . . . ”: Prompting Language Models Improves Quoting from Pre-Training Data (2023) — 63 citations
• One-Shot Learning from a Demonstration with Hierarchical Latent Language (2022) — 8 citations
• Probing Neural Language Models for Human Tacit Assumptions (2020) — 40 citations