Franco Maria Nardini

Artificial Intelligence · 2016–2020

A researcher in the Science corpus: 4 papers; trusts 45 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 78 citations into it; #31,495 of 35,345 by trust here, #16,471 by citations
• Information Retrieval & Search — 50 citations into it
• Information Systems — 35 citations into it; #7,517 of 8,771 by trust here, #3,012 by citations
• Computer Vision and Pattern Recognition — 32 citations into it
• Natural Language Processing — 21 citations into it
• Large Language Models — 14 citations into it
• Optimization & Training — 7 citations into it
• Management Science and Operations Research — 6 citations into it

Whom Franco Maria Nardini trusts overall

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

1. Diederik P. Kingma
2. Rodrigo Nogueira
3. Zhuyun Dai
4. Yoshua Bengio
5. Geoffrey E. Hinton
6. Jacob Devlin
7. Kyunghyun Cho
8. Jimmy J. Lin
9. Jimmy Ba
10. Wei Yang

Who trusts Franco Maria Nardini overall

1. Sebastian Hofstätter
2. Thibault Formal
3. Antonio Mallia
4. Omar Khattab

Papers from Franco Maria Nardini's perspective

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

1. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
2. ImageNet classification with deep convolutional neural networks
3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
4. Attention is All you Need (Neural Information Processing Systems)
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. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
10. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)

Their papers

• Efficient Document Re-Ranking for Transformers by Precomputing Term Representations (2020) — 132 citations
• Quality versus efficiency in document scoring with learning-to-rank models (2016) — 59 citations
• Expansion via Prediction of Importance with Contextualization (2020) — 122 citations
• Training Curricula for Open Domain Answer Re-Ranking (2020) — 20 citations