Allyson Ettinger
Artificial Intelligence · 2016–2023
A researcher in the Science corpus: 5 papers; trusts 155 researchers and is trusted by 131 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 113 citations into it; #1,718 of 35,345 by trust here, #5,317 by citations
- Natural Language Processing — 94 citations into it; #508 of 5,688 by trust here, #1,286 by citations
- Computer Vision and Pattern Recognition — 25 citations into it
- Representation & Self-Supervised Learning — 24 citations into it; #1,765 of 3,145 by trust here, #2,217 by citations
- Large Language Models — 19 citations into it
- Evaluation & Benchmarks — 18 citations into it; #318 of 3,147 by trust here, #1,467 by citations
- Computational Linguistics & Semantics — 14 citations into it
- Model Architectures — 13 citations into it
Whom Allyson Ettinger trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Richard Socher
- Geoffrey E. Hinton
- Yoav Goldberg
- Yoshua Bengio
- Christopher D. Manning
- Philip Resnik
- Diederik P. Kingma
- Tomas Mikolov
- Ilya Sutskever
- Alex Krizhevsky
Who trusts Allyson Ettinger overall
- Timo Schick
- Alex Warstadt
- Hinrich Schütze
- Yonatan Belinkov
- Samuel R. Bowman
- Nora Kassner
- Abhilasha Ravichander
- Douwe Kiela
- Yian Zhang
- Ellie Pavlick
Papers from Allyson Ettinger's perspective
Ordered by how strongly the researchers Allyson Ettinger 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
- Attention is All you Need (Neural Information Processing Systems)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
Their papers
- Towards Linguistically Generalizable NLP Systems: A Workshop and Shared Task (2017) — 95 citations
- Probing for semantic evidence of composition by means of simple classification tasks (2016) — 168 citations
- What BERT Is Not: Lessons from a New Suite of Psycholinguistic Diagnostics for Language Models (2019) — 680 citations
- Assessing Composition in Sentence Vector Representations (2018) — 84 citations
- Faith and Fate: Limits of Transformers on Compositionality (2023) — 650 citations