Hady ElSahar

Artificial Intelligence · 2017–2023

A researcher in the Science corpus: 13 papers; trusts 262 researchers and is trusted by 13 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 408 citations into it; #9,292 of 35,345 by trust here, #4,979 by citations
• Natural Language Processing — 280 citations into it; #2,086 of 5,688 by trust here, #1,466 by citations
• Computer Vision and Pattern Recognition — 111 citations into it
• Evaluation & Benchmarks — 108 citations into it
• Large Language Models — 103 citations into it
• Reinforcement Learning — 50 citations into it
• Model Architectures — 43 citations into it
• Safety, Robustness & Interpretability — 39 citations into it

Whom Hady ElSahar trusts overall

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

1. Geoffrey E. Hinton
2. Ronald J. Williams
3. Yoshua Bengio
4. Ilya Sutskever
5. Yann LeCun
6. Diederik P. Kingma
7. Alex Krizhevsky
8. Richard S. Sutton
9. Marc'Aurelio Ranzato
10. Oriol Vinyals

Who trusts Hady ElSahar overall

1. Tomasz Korbak
2. Nina Poerner
3. Hinrich Schütze
4. Nora Kassner
5. Germán Kruszewski
6. Ethan Perez
7. Zexuan Zhong
8. Fabio Petroni
9. Bryan Eikema
10. Guanghui Qin

Papers from Hady ElSahar's perspective

Ordered by how strongly the researchers Hady ElSahar 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. ImageNet: A large-scale hierarchical image database
8. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
9. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
10. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)

Their papers

• T-REx: A Large Scale Alignment of Natural Language with Knowledge Base Triples (2018) — 381 citations
• What Language Model to Train if You Have One Million GPU Hours? (2022) — 125 citations
• A Distributional Approach to Controlled Text Generation (2020) — 140 citations
• On Reinforcement Learning and Distribution Matching for Fine-Tuning Language Models with no Catastrophic Forgetting (2022) — 94 citations
• Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages (2020) — 322 citations
• Neural Wikipedian: Generating Textual Summaries from Knowledge Base Triples (2017) — 70 citations
• Controlling Conditional Language Models without Catastrophic Forgetting (2021) — 43 citations
• Energy-Based Models for Code Generation under Compilability Constraints (2021) — 14 citations
• Seamless: Multilingual Expressive and Streaming Speech Translation (2023) — 299 citations
• SeamlessM4T: Massively Multilingual&Multimodal Machine Translation (2023) — 202 citations
• BLOOM: A 176B-Parameter Open-Access Multilingual Language Model (2022) — 2,975 citations
• Documenting Geographically and Contextually Diverse Data Sources: The BigScience Catalogue of Language Data and Resources (2022) — 14 citations
• References in Wikipedia: The Editors’ Perspective (2021) — 9 citations