Beliz Gunel

Artificial Intelligence · 2020

A researcher in the Science corpus: 3 papers; trusts 164 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 98 citations into it
• Natural Language Processing — 72 citations into it; #5,018 of 5,688 by trust here, #3,826 by citations
• Computer Vision and Pattern Recognition — 53 citations into it
• Representation & Self-Supervised Learning — 43 citations into it; #2,812 of 3,145 by trust here, #1,982 by citations
• Evaluation & Benchmarks — 23 citations into it
• Large Language Models — 16 citations into it
• Model Architectures — 8 citations into it

Whom Beliz Gunel trusts overall

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

1. Geoffrey E. Hinton
2. Alex Krizhevsky
3. Yoshua Bengio
4. Kaiming He
5. Diederik P. Kingma
6. Yann LeCun
7. Ilya Sutskever
8. Jacob Devlin
9. Alex Graves
10. Quoc V. Le

Who trusts Beliz Gunel overall

1. Shuyang Cao
2. Katikapalli Subramanyam Kalyan
3. Yifan Zhang
4. Sinong Wang
5. Anastasia Razdaibiedina
6. Lu Wang
7. Ziwei Ji
8. Tu Vu
9. Ajit Rajasekharan
10. Bryan Hooi

Papers from Beliz Gunel's perspective

Ordered by how strongly the researchers Beliz Gunel 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Attention is All you Need (Neural Information Processing Systems)
5. Long Short-Term Memory
6. ImageNet: A large-scale hierarchical image database
7. Gradient-based learning applied to document recognition
8. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
9. ImageNet Large Scale Visual Recognition Challenge
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• Self-training Improves Pre-training for Natural Language Understanding (2020) — 173 citations
• Mind The Facts: Knowledge-Boosted Coherent Abstractive Text Summarization (2020) — 44 citations
• Supervised Contrastive Learning for Pre-trained Language Model Fine-tuning (2020) — 614 citations