X. Kong

Artificial Intelligence · with Anastasopoulos · 2018–2020

A researcher in the Science corpus: 4 papers; trusts 314 researchers and is trusted by 11 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 106 citations into it; #13,717 of 35,345 by trust here, #19,439 by citations
• Natural Language Processing — 90 citations into it
• Computer Vision and Pattern Recognition — 71 citations into it; #19,141 of 21,575 by trust here, #13,815 by citations
• Model Architectures — 22 citations into it
• Generative Models — 9 citations into it
• Efficiency & Compression — 8 citations into it
• Evaluation & Benchmarks — 8 citations into it
• Machine Translation — 6 citations into it; #79 of 292 by trust here, #133 by citations

Whom X. Kong trusts overall

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

1. Geoffrey E. Hinton
2. Ilya Sutskever
3. Yoshua Bengio
4. Diederik P. Kingma
5. Oriol Vinyals
6. Alex Graves
7. Ashish Vaswani
8. Alex Krizhevsky
9. Dzmitry Bahdanau
10. Kyunghyun Cho

Who trusts X. Kong overall

1. Huiwen Chang
2. Xin Sun
3. José Lezama
4. Xiang Dai
5. Ziwei Ji
6. Felix Stahlberg
7. Tao Ge
8. Sufeng Duan
9. Surafel Melaku Lakew

Papers from X. Kong's perspective

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

Their papers

• Deep Transformers with Latent Depth (2020) — 31 citations
• Generalized Data Augmentation for Low-Resource Translation (2019) — 128 citations
• Fully Non-autoregressive Neural Machine Translation: Tricks of the Trade (2020) — 155 citations
• Neural Machine Translation with Adequacy-Oriented Learning (2018) — 27 citations