Xuanwei Zhang

Artificial Intelligence · 2020–2021

A researcher in the Science corpus: 5 papers; trusts 43 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 86 citations into it; #24,789 of 35,345 by trust here, #10,065 by citations
• Natural Language Processing — 66 citations into it; #4,138 of 5,688 by trust here, #2,846 by citations
• Large Language Models — 52 citations into it
• Computer Vision and Pattern Recognition — 40 citations into it; #15,254 of 21,575 by trust here, #14,822 by citations
• Evaluation & Benchmarks — 24 citations into it; #2,214 of 3,147 by trust here, #1,603 by citations
• General Social Sciences — 5 citations into it

Whom Xuanwei Zhang trusts overall

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

1. Jacob Devlin
2. Geoffrey E. Hinton
3. Alex Wang
4. Ilya Sutskever
5. Yoshua Bengio
6. Ashish Vaswani
7. Diederik P. Kingma
8. Wanxiang Che
9. Adina Williams
10. Alec Radford

Who trusts Xuanwei Zhang overall

1. Abeba Birhane
2. Katikapalli Subramanyam Kalyan
3. Wei Zeng
4. Hai Hu
5. Vinay Uday Prabhu
6. Junyang Lin
7. Ajit Rajasekharan
8. Lu Li
9. Emmanuel Kahembwe
10. Xiao Liu

Papers from Xuanwei Zhang's perspective

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

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

• Yuan 1.0: Large-Scale Pre-trained Language Model in Zero-Shot and Few-Shot Learning (2021) — 69 citations
• FewCLUE: A Chinese Few-shot Learning Evaluation Benchmark (2021) — 59 citations
• CLUE: A Chinese Language Understanding Evaluation Benchmark (2020) — 460 citations
• CLUECorpus2020: A Large-scale Chinese Corpus for Pre-training Language Model (2020) — 81 citations
• Light Pre-Trained Chinese Language Model for NLP Tasks (2020)