Elena Voita

Artificial Intelligence · 2018–2020

A researcher in the Science corpus: 5 papers; trusts 237 researchers and is trusted by 51 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 118 citations into it; #6,983 of 35,345 by trust here, #4,137 by citations
• Natural Language Processing — 102 citations into it; #1,244 of 5,688 by trust here, #1,926 by citations
• Computer Vision and Pattern Recognition — 50 citations into it; #13,840 of 21,575 by trust here, #9,563 by citations
• Evaluation & Benchmarks — 23 citations into it; #646 of 3,147 by trust here, #1,764 by citations
• Representation & Self-Supervised Learning — 15 citations into it
• Large Language Models — 12 citations into it; #302 of 799 by trust here, #586 by citations
• Model Architectures — 12 citations into it; #663 of 2,278 by trust here, #501 by citations
• Efficiency & Compression — 7 citations into it

Whom Elena Voita trusts overall

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

1. Diederik P. Kingma
2. Rico Sennrich
3. Yoshua Bengio
4. Geoffrey E. Hinton
5. Christopher D. Manning
6. Ilya Sutskever
7. Alex Krizhevsky
8. Jimmy Ba
9. Yann LeCun
10. Alex Graves

Who trusts Elena Voita overall

1. Yonatan Belinkov
2. Amil Merchant
3. Ethan Perez
4. Julian Michael
5. Maithra Raghu
6. Tiago Pimentel
7. Charles Lovering
8. J. O’Connor
9. Hila Chefer
10. Douwe Kiela

Papers from Elena Voita's perspective

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

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

Their papers

• Analyzing Multi-Head Self-Attention: Specialized Heads Do the Heavy Lifting, the Rest Can Be Pruned (2019) — 1,560 citations
• The Bottom-up Evolution of Representations in the Transformer: A Study with Machine Translation and Language Modeling Objectives (2019) — 221 citations
• BPE-Dropout: Simple and Effective Subword Regularization (2019) — 344 citations
• Context-Aware Neural Machine Translation Learns Anaphora Resolution (2018) — 322 citations
• Information-Theoretic Probing with Minimum Description Length (2020) — 324 citations