Emilio Monti

Natural Language Processing · 2017–2020

A researcher in the Science corpus: 2 papers; trusts 64 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

• Natural Language Processing — 42 citations into it
• Artificial Intelligence — 40 citations into it; #25,217 of 35,345 by trust here, #26,682 by citations
• Computer Vision and Pattern Recognition — 11 citations into it; #15,615 of 21,575 by trust here, #17,258 by citations
• Model Architectures — 7 citations into it
• Representation & Self-Supervised Learning — 6 citations into it

Whom Emilio Monti trusts overall

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

1. Geoffrey E. Hinton
2. Yoshua Bengio
3. Diederik P. Kingma
4. Oriol Vinyals
5. Ilya Sutskever
6. Kyunghyun Cho
7. Dzmitry Bahdanau
8. Alex Krizhevsky
9. Luke S. Zettlemoyer
10. Richard Socher

Who trusts Emilio Monti overall

1. Jianpeng Cheng
2. Qile Zhu
3. Marco Damonte
4. Siva Reddy
5. Sonal Gupta
6. Young-Bum Kim

Papers from Emilio Monti's perspective

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

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

Their papers

• Transfer Learning for Neural Semantic Parsing (2017) — 65 citations
• Don’t Parse, Generate! A Sequence to Sequence Architecture for Task-Oriented Semantic Parsing (2020) — 100 citations