Muhammad Abdul-Mageed

Artificial Intelligence · 2016–2020

A researcher in the Science corpus: 4 papers; trusts 194 researchers and is trusted by 11 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 109 citations into it; #12,123 of 35,345 by trust here, #15,004 by citations
• Natural Language Processing — 80 citations into it; #4,791 of 5,688 by trust here, #4,250 by citations
• Computer Vision and Pattern Recognition — 26 citations into it
• Large Language Models — 25 citations into it
• Model Architectures — 15 citations into it
• Representation & Self-Supervised Learning — 13 citations into it
• Evaluation & Benchmarks — 11 citations into it; #2,519 of 3,147 by trust here, #2,545 by citations
• Safety, Robustness & Interpretability — 10 citations into it

Whom Muhammad Abdul-Mageed trusts overall

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

1. Alex Graves
2. Geoffrey E. Hinton
3. Yoshua Bengio
4. Diederik P. Kingma
5. Ilya Sutskever
6. Yann LeCun
7. Alex Krizhevsky
8. Richard Socher
9. J. Urgen Schmidhuber
10. Tomas Mikolov

Who trusts Muhammad Abdul-Mageed overall

1. Sven Buechel
2. Lei Zhang
3. Ramit Sawhney
4. Elvis Saravia
5. Irene Solaiman
6. Udo Hahn
7. Saif M. Mohammad
8. Shuai Wang
9. Harshit Joshi
10. Hsien-Chi Toby Liu

Papers from Muhammad Abdul-Mageed's perspective

Ordered by how strongly the researchers Muhammad Abdul-Mageed 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. ImageNet classification with deep convolutional neural networks
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. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
8. ImageNet: A large-scale hierarchical image database
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

• Does ‘well-being’ translate on Twitter? (2016) — 12 citations
• Automatic Detection of Machine Generated Text: A Critical Survey (2020) — 305 citations
• ARBERT & MARBERT: Deep Bidirectional Transformers for Arabic (2020) — 689 citations
• EmoNet: Fine-Grained Emotion Detection with Gated Recurrent Neural Networks (2017) — 320 citations