Vladimir Karpukhin

Artificial Intelligence · 2020–2022

A researcher in the Science corpus: 7 papers; trusts 104 researchers and is trusted by 81 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 274 citations into it; #3,540 of 35,345 by trust here, #1,870 by citations
• Natural Language Processing — 203 citations into it
• Computer Vision and Pattern Recognition — 153 citations into it
• Information Retrieval & Search — 108 citations into it; #97 of 1,022 by trust here, #6 by citations
• Evaluation & Benchmarks — 71 citations into it
• Large Language Models — 56 citations into it
• Retrieval-Augmented Generation — 26 citations into it; #8 of 99 by trust here, #3 by citations
• Management Science and Operations Research — 21 citations into it

Whom Vladimir Karpukhin trusts overall

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

1. Diederik P. Kingma
2. Geoffrey E. Hinton
3. Yoshua Bengio
4. Kenton C. T. Lee
5. Ilya Sutskever
6. Yann LeCun
7. Alex Krizhevsky
8. Jimmy Ba
9. Kaiming He
10. Jacob Devlin

Who trusts Vladimir Karpukhin overall

1. Luyu Gao
2. Gautier Izacard
3. Akari Asai
4. Fabio Petroni
5. Patrick Lewis
6. Jimmy J. Lin
7. Omar Khattab
8. Xueguang Ma
9. Danqi Chen
10. Sebastian Hofstätter

Papers from Vladimir Karpukhin's perspective

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

1. Attention is All you Need (Neural Information Processing Systems)
2. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
4. ImageNet classification with deep convolutional neural networks
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

• Dense Passage Retrieval for Open-Domain Question Answering (2020) — 6,334 citations
• CM3: A Causal Masked Multimodal Model of the Internet (2022) — 180 citations
• The Web Is Your Oyster - Knowledge-Intensive NLP against a Very Large Web Corpus (2021) — 79 citations
• Domain-matched Pre-training Tasks for Dense Retrieval (2021) — 72 citations
• UniK-QA: Unified Representations of Structured and Unstructured Knowledge for Open-Domain Question Answering (2020) — 106 citations
• Multi-Task Retrieval for Knowledge-Intensive Tasks (2021) — 69 citations
• Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks (2020) — 16,110 citations