Lucas Hosseini

Artificial Intelligence · 2020–2024

A researcher in the Science corpus: 6 papers; trusts 274 researchers and is trusted by 4 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 244 citations into it; #25,810 of 35,345 by trust here, #4,682 by citations
• Computer Vision and Pattern Recognition — 145 citations into it; #15,948 of 21,575 by trust here, #3,582 by citations
• Natural Language Processing — 137 citations into it
• Information Retrieval & Search — 135 citations into it; #653 of 1,022 by trust here, #183 by citations
• Representation & Self-Supervised Learning — 48 citations into it; #3,023 of 3,145 by trust here, #1,138 by citations
• Evaluation & Benchmarks — 47 citations into it
• Large Language Models — 44 citations into it
• Retrieval-Augmented Generation — 32 citations into it

Whom Lucas Hosseini trusts overall

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

1. Geoffrey E. Hinton
2. Yoshua Bengio
3. Kaiming He
4. Diederik P. Kingma
5. Ilya Sutskever
6. Alex Krizhevsky
7. Gautier Izacard
8. Tomas Mikolov
9. Yann LeCun
10. Kenton C. T. Lee

Who trusts Lucas Hosseini overall

1. Akari Asai
2. Niklas Muennighoff
3. Alex Troy Mallen
4. Patrick Lewis
5. Liang Wang
6. Sewon Min
7. Luyu Gao
8. Gautier Izacard
9. Xilun Chen
10. Weijia Shi

Papers from Lucas Hosseini's perspective

Ordered by how strongly the researchers Lucas Hosseini 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. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
7. ImageNet: A large-scale hierarchical image database
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

• Few-shot Learning with Retrieval Augmented Language Models (2022) — 1,295 citations
• Unsupervised Dense Information Retrieval with Contrastive Learning (2021) — 1,593 citations
• A Memory Efficient Baseline for Open Domain Question Answering (2020) — 46 citations
• Improving Wikipedia verifiability with AI (2022) — 23 citations
• The Faiss Library (2024) — 768 citations
• Towards Unsupervised Dense Information Retrieval with Contrastive Learning (2021) — 142 citations