Eyal Ben-David

Artificial Intelligence · 2021

A researcher in the Science corpus: 2 papers; trusts 59 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 68 citations into it
• Natural Language Processing — 38 citations into it
• Large Language Models — 21 citations into it
• Computer Vision and Pattern Recognition — 17 citations into it
• Representation & Self-Supervised Learning — 17 citations into it
• Prompting & Reasoning — 10 citations into it
• Evaluation & Benchmarks — 7 citations into it

Whom Eyal Ben-David trusts overall

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

1. Diederik P. Kingma
2. Yoshua Bengio
3. Geoffrey E. Hinton
4. Jimmy Ba
5. Alec Radford
6. Xiaochuang Han
7. Chin-Yew Lin
8. Hal Daumé Iii
9. Ilya Sutskever
10. Alex Krizhevsky

Who trusts Eyal Ben-David overall

1. Pengfei Liu
2. Yongchao Zhou
3. Bonan Min
4. Weizhe Yuan
5. Chengwei Qin

Papers from Eyal Ben-David's perspective

Ordered by how strongly the researchers Eyal Ben-David 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. Attention is All you Need (Neural Information Processing Systems)
4. ImageNet classification with deep convolutional neural networks
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. 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

• PADA: Example-based Prompt Learning for on-the-fly Adaptation to Unseen Domains (2021) — 103 citations
• PADA: A Prompt-based Autoregressive Approach for Adaptation to Unseen Domains (2021) — 70 citations