Haotang Deng

Artificial Intelligence · 2019–2020

A researcher in the Science corpus: 3 papers; trusts 27 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 50 citations into it; #29,917 of 35,345 by trust here, #9,170 by citations
• Natural Language Processing — 42 citations into it
• Large Language Models — 21 citations into it; #607 of 799 by trust here, #564 by citations

Whom Haotang Deng trusts overall

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

1. Geoffrey E. Hinton
2. Yoshua Bengio
3. Alec Radford
4. Jacob Devlin
5. Ilya Sutskever
6. Diederik P. Kingma
7. Alex Graves
8. Alex Krizhevsky
9. Yann LeCun
10. Tomas Mikolov

Who trusts Haotang Deng overall

1. Canwen Xu

Papers from Haotang Deng's perspective

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

1. Attention is All you Need (Neural Information Processing Systems)
2. Long Short-Term Memory
3. ImageNet classification with deep convolutional neural networks
4. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
5. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
6. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
7. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
8. Gradient-based learning applied to document recognition
9. Distributed Representations of Words and Phrases and their Compositionality (Neural Information Processing Systems)
10. ImageNet: A large-scale hierarchical image database

Their papers

• K-BERT: Enabling Language Representation with Knowledge Graph (2019) — 930 citations
• FastBERT: a Self-distilling BERT with Adaptive Inference Time (2020) — 436 citations
• UER: An Open-Source Toolkit for Pre-training Models (2019) — 145 citations