Francesca Toni

Artificial Intelligence · 2007–2021

A researcher in the Science corpus: 6 papers; trusts 342 researchers and is trusted by 9 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 185 citations into it; #12,032 of 35,345 by trust here, #13,163 by citations
• Natural Language Processing — 116 citations into it; #2,921 of 5,688 by trust here, #3,638 by citations
• Safety, Robustness & Interpretability — 69 citations into it; #1,725 of 2,251 by trust here, #2,041 by citations
• Computer Vision and Pattern Recognition — 37 citations into it
• Sociology and Political Science — 32 citations into it; #14,262 of 22,756 by trust here, #11,516 by citations
• Evaluation & Benchmarks — 29 citations into it
• Information Systems — 23 citations into it
• Large Language Models — 13 citations into it

Whom Francesca Toni trusts overall

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

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

Who trusts Francesca Toni overall

1. Sarah Wiegreffe
2. Piyawat Lertvittayakumjorn
3. Ana Marasovic
4. Neema Kotonya
5. Andrew Kyle Lampinen
6. Andreas Vlachos
7. Trevor J. M. Bench-Capon
8. Martin Wigbertus Antonius Caminada
9. Amrith Krishna
10. Zhijiang Guo

Papers from Francesca Toni's perspective

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

• Explanation-Based Human Debugging of NLP Models: A Survey (2021) — 90 citations
• Explainable Automated Fact-Checking for Public Health Claims (2020) — 357 citations
• Human-grounded Evaluations of Explanation Methods for Text Classification (2019) — 73 citations
• Explainable Automated Fact-Checking: A Survey (2020) — 153 citations
• Human-in-the-loop Debugging Deep Text Classifiers (2020) — 57 citations
• Computing ideal sceptical argumentation (2007) — 452 citations