Ekaterina Shutova
Artificial Intelligence · 2018–2022
A researcher in the Science corpus: 7 papers; trusts 201 researchers and is trusted by 4 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 165 citations into it; #19,499 of 35,345 by trust here, #16,166 by citations
- Natural Language Processing — 93 citations into it; #4,703 of 5,688 by trust here, #4,250 by citations
- Computer Vision and Pattern Recognition — 52 citations into it
- Safety, Robustness & Interpretability — 52 citations into it; #1,628 of 2,251 by trust here, #1,907 by citations
- Representation & Self-Supervised Learning — 34 citations into it
- Information Systems — 30 citations into it; #5,700 of 8,771 by trust here, #5,501 by citations
- Communication — 17 citations into it
- Social Psychology — 17 citations into it
Whom Ekaterina Shutova trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Diederik P. Kingma
- Geoffrey E. Hinton
- Yoshua Bengio
- Alex Krizhevsky
- Ilya Sutskever
- Sepp Hochreiter
- J. Urgen Schmidhuber
- Yann LeCun
- Jimmy Ba
- Tomas Mikolov
Who trusts Ekaterina Shutova overall
Papers from Ekaterina Shutova's perspective
Ordered by how strongly the researchers Ekaterina Shutova trusts endorse each paper. Same corpus, a different order for every researcher.
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- Gradient-based learning applied to document recognition
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- ImageNet: A large-scale hierarchical image database
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
Their papers
- A Multimodal Framework for the Detection of Hateful Memes (2020) — 103 citations
- Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models (2022) — 2,561 citations
- Stepmothers are mean and academics are pretentious: What do pretrained language models learn about you? (2021) — 32 citations
- Meta-Learning with Sparse Experience Replay for Lifelong Language Learning (2020) — 25 citations
- Joint Modelling of Emotion and Abusive Language Detection (2020) — 61 citations
- Tackling Online Abuse: A Survey of Automated Abuse Detection Methods (2019) — 92 citations
- Neural Character-based Composition Models for Abuse Detection (2018) — 63 citations