Jason Naradowsky

Artificial Intelligence · 2016–2020

A researcher in the Science corpus: 4 papers; trusts 92 researchers and is trusted by 136 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 89 citations into it; #1,983 of 35,345 by trust here, #2,208 by citations
• Natural Language Processing — 73 citations into it; #577 of 5,688 by trust here, #522 by citations
• Computer Vision and Pattern Recognition — 26 citations into it; #10,733 of 21,575 by trust here, #9,079 by citations
• Evaluation & Benchmarks — 20 citations into it
• Safety, Robustness & Interpretability — 14 citations into it; #371 of 2,251 by trust here, #339 by citations
• Signal Processing — 12 citations into it; #6,101 of 7,572 by trust here, #7,324 by citations
• Optimization & Training — 6 citations into it

Whom Jason Naradowsky trusts overall

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

1. Geoffrey E. Hinton
2. Christopher D. Manning
3. Yoshua Bengio
4. Ilya Sutskever
5. Diederik P. Kingma
6. Alex Krizhevsky
7. Steven Bird
8. Alex Graves
9. Richard Socher
10. Yann LeCun

Who trusts Jason Naradowsky overall

1. Yonatan Belinkov
2. Kawin Ethayarajh
3. Adam Poliak
4. Sunipa Dev
5. Rachel Rudinger
6. Samuel R. Bowman
7. Adina Williams
8. Matt Gardner
9. Jieyu Zhao
10. Emily Sheng

Papers from Jason Naradowsky's perspective

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

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

Their papers

• Gender Bias in Coreference Resolution (2018) — 750 citations
• Hypothesis Only Baselines in Natural Language Inference (2018) — 638 citations
• Programming with a Differentiable Forth Interpreter (2016) — 157 citations
• Meta-Learning Extractors for Music Source Separation (2020) — 68 citations