Wangchunshu Zhou

Artificial Intelligence · 2019–2022

A researcher in the Science corpus: 10 papers; trusts 472 researchers and is trusted by 9 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 256 citations into it; #14,189 of 35,345 by trust here, #5,749 by citations
• Natural Language Processing — 185 citations into it; #3,783 of 5,688 by trust here, #1,910 by citations
• Computer Vision and Pattern Recognition — 133 citations into it; #19,665 of 21,575 by trust here, #6,206 by citations
• Large Language Models — 65 citations into it; #422 of 799 by trust here, #513 by citations
• Evaluation & Benchmarks — 63 citations into it; #2,170 of 3,147 by trust here, #1,431 by citations
• Efficiency & Compression — 57 citations into it; #727 of 1,264 by trust here, #673 by citations
• Model Architectures — 32 citations into it
• Representation & Self-Supervised Learning — 20 citations into it

Whom Wangchunshu Zhou trusts overall

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

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

Who trusts Wangchunshu Zhou overall

1. Canwen Xu
2. Asli Celikyilmaz
3. Xipeng Qiu
4. Ji Xin
5. Young Jin Kim
6. Tianyu Wu
7. Peter Hase
8. Jiazheng Xu
9. Tao Ge
10. Julian McAuley

Papers from Wangchunshu Zhou's perspective

Ordered by how strongly the researchers Wangchunshu Zhou 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. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• CommonGen: A Constrained Text Generation Challenge for Generative Commonsense Reasoning (2020) — 417 citations
• Learning to Compare for Better Training and Evaluation of Open Domain Natural Language Generation Models (2020) — 50 citations
• BERT-of-Theseus: Compressing BERT by Progressive Module Replacing (2020) — 228 citations
• Towards Interpretable Natural Language Understanding with Explanations as Latent Variables (2020) — 50 citations
• BERT Loses Patience: Fast and Robust Inference with Early Exit (2020) — 447 citations
• Pre-training Text-to-Text Transformers for Concept-centric Common Sense (2020) — 73 citations
• Beyond Preserved Accuracy: Evaluating Loyalty and Robustness of BERT Compression (2021) — 47 citations
• VLUE: A Multi-Task Multi-Dimension Benchmark for Evaluating Vision-Language Pre-training (2022) — 17 citations
• Self-Adversarial Learning with Comparative Discrimination for Text Generation (2020) — 20 citations
• Improving Grammatical Error Correction with Machine Translation Pairs (2019) — 43 citations