Aaron Steven White
Natural Language Processing · 2017–2020
A researcher in the Science corpus: 7 papers; trusts 135 researchers and is trusted by 13 researchers here, as inferred from the citation graph.
Subfields
- Natural Language Processing — 137 citations into it; #2,081 of 5,688 by trust here, #3,574 by citations
- Artificial Intelligence — 132 citations into it
- Evaluation & Benchmarks — 37 citations into it; #1,546 of 3,147 by trust here, #2,330 by citations
- Computer Vision and Pattern Recognition — 36 citations into it
- Representation & Self-Supervised Learning — 16 citations into it
- Model Architectures — 8 citations into it
- Signal Processing — 5 citations into it
Whom Aaron Steven White trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Ilya Sutskever
- Sepp Hochreiter
- Alex Graves
- Geoffrey E. Hinton
- Diederik P. Kingma
- Yoshua Bengio
- J. Urgen Schmidhuber
- Matthew D. Zeiler
- Oriol Vinyals
- Richard Socher
Who trusts Aaron Steven White overall
- Ellie Pavlick
- Adam Poliak
- R. Thomas McCoy
- Rachel Rudinger
- Shane Storks
- Tom Kwiatkowski
- Yonatan Belinkov
- Benjamin Van Durme
- Adina Williams
- Reid Pryzant
Papers from Aaron Steven White's perspective
Ordered by how strongly the researchers Aaron Steven White trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- Gradient-based learning applied to document recognition
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
- ImageNet: A large-scale hierarchical image database
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
Their papers
- Lexicosyntactic Inference in Neural Models (2018) — 39 citations
- Collecting Diverse Natural Language Inference Problems for Sentence Representation Evaluation (2018) — 10 citations
- Performance of the ATLAS muon triggers in Run 2 (2020) — 358 citations
- Neural Models of Factuality (2018) — 89 citations
- Towards a Unified Natural Language Inference Framework to Evaluate Sentence Representations (2018) — 12 citations
- Inference is Everything: Recasting Semantic Resources into a Unified Evaluation Framework (2017) — 89 citations
- The role of veridicality and factivity in clause selection * (2017)