Elior Sulem

Artificial Intelligence · 2018–2021

A researcher in the Science corpus: 2 papers; trusts 54 researchers and is trusted by 4 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 225 citations into it; #23,529 of 35,345 by trust here, #16,771 by citations
• Natural Language Processing — 156 citations into it; #3,946 of 5,688 by trust here, #4,682 by citations
• Evaluation & Benchmarks — 31 citations into it; #2,087 of 3,147 by trust here, #2,743 by citations
• Molecular Biology — 10 citations into it

Whom Elior Sulem trusts overall

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

1. Steven Bird
2. Yvette Graham
3. Yoshua Bengio
4. Geoffrey E. Hinton
5. Diederik P. Kingma
6. Ilya Sutskever
7. Philipp Koehn
8. Alex Krizhevsky
9. Tomas Mikolov
10. Yann LeCun

Who trusts Elior Sulem overall

1. Fernando Alva-Manchego
2. Louis Martin
3. Carolina Scarton
4. Thomas Scialom
5. Sebastian Gehrmann

Papers from Elior Sulem's perspective

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

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

Their papers

• BLEU is Not Suitable for the Evaluation of Text Simplification (2018) — 225 citations
• Recent Advances in Natural Language Processing via Large Pre-trained Language Models: A Survey (2021) — 1,575 citations