Rabeeh Karimi Mahabadi

Artificial Intelligence · 2015–2022

A researcher in the Science corpus: 3 papers; trusts 137 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 81 citations into it
• Natural Language Processing — 58 citations into it
• Computer Vision and Pattern Recognition — 49 citations into it
• Large Language Models — 27 citations into it
• Prompting & Reasoning — 16 citations into it
• Evaluation & Benchmarks — 15 citations into it
• Model Architectures — 10 citations into it; #1,720 of 2,278 by trust here, #1,665 by citations
• Representation & Self-Supervised Learning — 9 citations into it

Whom Rabeeh Karimi Mahabadi trusts overall

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

1. Geoffrey E. Hinton
2. Yoshua Bengio
3. Diederik P. Kingma
4. Alex Krizhevsky
5. Ilya Sutskever
6. Kaiming He
7. Yann LeCun
8. Richard Socher
9. Alec Radford
10. Jimmy Ba

Who trusts Rabeeh Karimi Mahabadi overall

1. Yi-Lin Sung
2. Dongze Lian
3. Zeyu Han
4. Lingling Xu
5. Shih-Yang Liu
6. Runxin Xu
7. Yuning Mao
8. Jaemin Cho
9. Lewis Tunstall
10. Varun Nair

Papers from Rabeeh Karimi Mahabadi's perspective

Ordered by how strongly the researchers Rabeeh Karimi Mahabadi 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Attention is All you Need (Neural Information Processing Systems)
5. Long Short-Term Memory
6. ImageNet: A large-scale hierarchical image database
7. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
8. Gradient-based learning applied to document recognition
9. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
10. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)

Their papers

• Prompt-free and Efficient Few-shot Learning with Language Models (2022) — 76 citations
• Parameter-efficient Multi-task Fine-tuning for Transformers via Shared Hypernetworks (2021) — 382 citations
• Segment based 3D object shape priors (2015) — 26 citations