Zhixing Tan

Artificial Intelligence · 2016–2021

A researcher in the Science corpus: 4 papers; trusts 95 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 104 citations into it; #29,600 of 35,345 by trust here, #12,387 by citations
• Natural Language Processing — 71 citations into it; #4,833 of 5,688 by trust here, #3,332 by citations
• Computer Vision and Pattern Recognition — 42 citations into it
• Large Language Models — 26 citations into it
• Model Architectures — 25 citations into it
• Optimization & Training — 11 citations into it
• Prompting & Reasoning — 11 citations into it
• Efficiency & Compression — 10 citations into it

Whom Zhixing Tan 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 Graves
6. Alex Krizhevsky
7. Jimmy Ba
8. Kaiming He
9. Yann LeCun
10. Dzmitry Bahdanau

Who trusts Zhixing Tan overall

1. Angela Fan
2. Dan Otter
3. Matthew E. Peters
4. Tianyi Zhou
5. Wanxiang Che
6. Nikhita Vedula
7. Jie Yang
8. Emma Strubell
9. Amirsina Torfi
10. Jacob Buckman

Papers from Zhixing Tan's perspective

Ordered by how strongly the researchers Zhixing Tan 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. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
9. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
10. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)

Their papers

• Deep Semantic Role Labeling with Self-Attention (2017) — 320 citations
• MSP: Multi-Stage Prompting for Making Pre-trained Language Models Better Translators (2021) — 59 citations
• Lattice-Based Recurrent Neural Network Encoders for Neural Machine Translation (2016) — 92 citations
• CPM-2: Large-scale Cost-effective Pre-trained Language Models (2021) — 101 citations