Chen Xing

Artificial Intelligence · 2016–2022

A researcher in the Science corpus: 9 papers; trusts 528 researchers and is trusted by 6 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 201 citations into it; #31,457 of 35,345 by trust here, #9,275 by citations
• Computer Vision and Pattern Recognition — 153 citations into it; #19,315 of 21,575 by trust here, #13,815 by citations
• Natural Language Processing — 98 citations into it
• Optimization & Training — 55 citations into it
• Representation & Self-Supervised Learning — 46 citations into it
• Model Architectures — 40 citations into it; #2,242 of 2,278 by trust here, #874 by citations
• Evaluation & Benchmarks — 26 citations into it
• Large Language Models — 24 citations into it

Whom Chen Xing trusts overall

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

1. Alex Krizhevsky
2. Geoffrey E. Hinton
3. Kaiming He
4. Diederik P. Kingma
5. Yoshua Bengio
6. Ilya Sutskever
7. Yann LeCun
8. Oriol Vinyals
9. Ross B. Girshick
10. Karen Simonyan

Who trusts Chen Xing overall

1. Stanislaw Jastrzebski
2. Charles H. Martin
3. Arnout Devos
4. Minlie Huang
5. Hongshen Chen
6. Jinghui Chen
7. Hao Zhou
8. Zhen Wang
9. Han-Jia Ye
10. Wei-Jen Ko

Papers from Chen Xing's perspective

Ordered by how strongly the researchers Chen Xing 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. Long Short-Term Memory
5. Attention is All you Need (Neural Information Processing Systems)
6. ImageNet: A large-scale hierarchical image database
7. Gradient-based learning applied to document recognition
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. ImageNet Large Scale Visual Recognition Challenge
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• Topic Aware Neural Response Generation (2016) — 490 citations
• Open Vocabulary Object Detection with Pseudo Bounding-Box Labels (2021) — 118 citations
• Adaptive Cross-Modal Few-Shot Learning (2019) — 339 citations
• On Layer Normalization in the Transformer Architecture (2020) — 1,522 citations
• A Walk with SGD (2018) — 145 citations
• Topic Augmented Neural Response Generation with a Joint Attention Mechanism (2016) — 49 citations
• ULIP: Learning a Unified Representation of Language, Images, and Point Clouds for 3D Understanding (2022) — 401 citations
• Improving Gender Fairness of Pre-Trained Language Models without Catastrophic Forgetting (2021) — 45 citations
• Taking Notes on the Fly Helps BERT Pre-training (2020) — 10 citations