Ke Xu

Artificial Intelligence · with Zhou · 2014–2020

A researcher in the Science corpus: 9 papers; trusts 346 researchers and is trusted by 21 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 175 citations into it; #9,510 of 35,345 by trust here, #4,797 by citations
• Natural Language Processing — 148 citations into it; #3,511 of 5,688 by trust here, #3,529 by citations
• Computer Vision and Pattern Recognition — 68 citations into it; #15,403 of 21,575 by trust here, #8,409 by citations
• Evaluation & Benchmarks — 43 citations into it; #2,204 of 3,147 by trust here, #2,627 by citations
• Large Language Models — 27 citations into it; #751 of 799 by trust here, #524 by citations
• Model Architectures — 24 citations into it
• Optimization & Training — 24 citations into it
• Representation & Self-Supervised Learning — 18 citations into it

Whom Ke Xu trusts overall

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

1. Yoshua Bengio
2. Geoffrey E. Hinton
3. Diederik P. Kingma
4. Ilya Sutskever
5. Alex Krizhevsky
6. Sepp Hochreiter
7. Yann LeCun
8. Alex Graves
9. Kaiming He
10. Oriol Vinyals

Who trusts Ke Xu overall

1. Asli Celikyilmaz
2. Tianyu Wu
3. Jiazheng Xu
4. Xiaohan Zou
5. Hongwei Wang
6. Duyu Tang

Papers from Ke Xu's perspective

Ordered by how strongly the researchers Ke Xu 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. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
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

• Question Answering over Freebase with Multi-Column Convolutional Neural Networks (2015) — 456 citations
• Learning to Compare for Better Training and Evaluation of Open Domain Natural Language Generation Models (2020) — 50 citations
• Visualizing and Understanding the Effectiveness of BERT (2019) — 205 citations
• BERT Loses Patience: Fast and Robust Inference with Early Exit (2020) — 447 citations
• Adaptive Recursive Neural Network for Target-dependent Twitter Sentiment Classification (2014) — 984 citations
• Self-Adversarial Learning with Comparative Discrimination for Text Generation (2020) — 20 citations
• Self-Attention Attribution: Interpreting Information Interactions Inside Transformer (2020) — 300 citations
• Improving Grammatical Error Correction with Machine Translation Pairs (2019) — 43 citations
• Can Online Emotions Predict the Stock Market in China? (2016) — 40 citations