Neema Kotonya

Artificial Intelligence · 2020–2022

A researcher in the Science corpus: 3 papers; trusts 163 researchers and is trusted by 5 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 77 citations into it; #15,730 of 35,345 by trust here, #17,776 by citations
• Natural Language Processing — 70 citations into it; #3,600 of 5,688 by trust here, #4,879 by citations
• Sociology and Political Science — 31 citations into it; #14,261 of 22,756 by trust here, #11,516 by citations
• Evaluation & Benchmarks — 30 citations into it
• Information Systems — 16 citations into it
• Safety, Robustness & Interpretability — 12 citations into it
• Computer Vision and Pattern Recognition — 10 citations into it
• Large Language Models — 7 citations into it

Whom Neema Kotonya trusts overall

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

1. Chin-Yew Lin
2. Andreas Vlachos
3. Geoffrey E. Hinton
4. Yoshua Bengio
5. Diederik P. Kingma
6. Yixin Nie
7. Ilya Sutskever
8. James Thorne
9. Michael Collins
10. Alex Krizhevsky

Who trusts Neema Kotonya overall

1. Sarah Wiegreffe
2. Ana Marasovic
3. Andreas Vlachos
4. Amrith Krishna
5. James Thorne
6. Zhijiang Guo
7. Sebastian Riedel
8. Rami Aly
9. Amelia Glaese

Papers from Neema Kotonya's perspective

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

1. Attention is All you Need (Neural Information Processing Systems)
2. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
4. Long Short-Term Memory
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. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
8. ImageNet: A large-scale hierarchical image database
9. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
10. Gradient-based learning applied to document recognition

Their papers

• Explainable Automated Fact-Checking for Public Health Claims (2020) — 357 citations
• Policy Compliance Detection via Expression Tree Inference (2022)
• Explainable Automated Fact-Checking: A Survey (2020) — 153 citations