Olga Kovaleva

Artificial Intelligence · 2019–2021

A researcher in the Science corpus: 4 papers; trusts 233 researchers and is trusted by 27 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 201 citations into it; #7,389 of 35,345 by trust here, #4,018 by citations
• Natural Language Processing — 128 citations into it
• Computer Vision and Pattern Recognition — 79 citations into it; #8,198 of 21,575 by trust here, #4,372 by citations
• Large Language Models — 62 citations into it; #222 of 799 by trust here, #360 by citations
• Efficiency & Compression — 38 citations into it
• Evaluation & Benchmarks — 36 citations into it; #2,592 of 3,147 by trust here, #2,393 by citations
• Model Architectures — 29 citations into it
• Representation & Self-Supervised Learning — 27 citations into it

Whom Olga Kovaleva trusts overall

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

1. Geoffrey E. Hinton
2. Yoshua Bengio
3. Diederik P. Kingma
4. Ilya Sutskever
5. Jacob Devlin
6. Richard Socher
7. Alex Krizhevsky
8. Alex Graves
9. Yann LeCun
10. Kaiming He

Who trusts Olga Kovaleva overall

1. Anna Rogers
2. Yen-Chun Chen
3. Yonatan Belinkov
4. Damian Pascual
5. Luca Soldaini
6. Jesse Vig
7. Mengjie Zhao
8. Piyawat Lertvittayakumjorn
9. Linjie Li
10. Anna Rumshisky

Papers from Olga Kovaleva's perspective

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

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

• A Primer in BERTology: What We Know About How BERT Works (2020) — 1,930 citations
• Revealing the Dark Secrets of BERT (2019) — 635 citations
• Getting Closer to AI Complete Question Answering: A Set of Prerequisite Real Tasks (2020) — 141 citations
• BERT Busters: Outlier Dimensions that Disrupt Transformers (2021) — 126 citations