Davood Rafiei

Artificial Intelligence · 2013–2023

A researcher in the Science corpus: 2 papers; trusts 66 researchers and is trusted by 1 researcher here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 37 citations into it; #33,512 of 35,345 by trust here, #23,731 by citations
• Natural Language Processing — 19 citations into it; #5,365 of 5,688 by trust here, #5,092 by citations
• Information Systems — 11 citations into it
• Large Language Models — 9 citations into it
• Prompting & Reasoning — 9 citations into it

Whom Davood Rafiei trusts overall

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

1. Sepp Hochreiter
2. J. Fleiss
3. Michael D. Conover
4. Geoffrey E. Hinton
5. Ilya Sutskever
6. Tao Yu
7. J. Urgen Schmidhuber
8. Yoshua Bengio
9. Jason Wei
10. Diederik P. Kingma

Who trusts Davood Rafiei overall

1. Ugur Kursuncu
2. Ruoxi Sun

Papers from Davood Rafiei's perspective

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

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

Their papers

• DIN-SQL: Decomposed In-Context Learning of Text-to-SQL with Self-Correction (2023) — 761 citations
• Predicting political preference of Twitter users (2013) — 153 citations