Artur Kulmizev

Artificial Intelligence · 2020–2021

A researcher in the Science corpus: 2 papers; trusts 60 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 59 citations into it
• Natural Language Processing — 53 citations into it
• Large Language Models — 18 citations into it
• Computer Vision and Pattern Recognition — 17 citations into it
• Representation & Self-Supervised Learning — 17 citations into it
• Evaluation & Benchmarks — 13 citations into it
• Safety, Robustness & Interpretability — 7 citations into it

Whom Artur Kulmizev trusts overall

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

1. Diederik P. Kingma
2. Geoffrey E. Hinton
3. Jimmy Ba
4. Tomas Mikolov
5. Yoshua Bengio
6. Richard Socher
7. Ilya Sutskever
8. Alex Krizhevsky
9. Kaiming He
10. Yann LeCun

Who trusts Artur Kulmizev overall

1. Roma Patel

Papers from Artur Kulmizev's perspective

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

Their papers

• Positional Artefacts Propagate Through Masked Language Model Embeddings (2020) — 46 citations
• Can Language Models Encode Perceptual Structure Without Grounding? A Case Study in Color (2021) — 178 citations