Zewen Chi

Artificial Intelligence · 2019–2023

A researcher in the Science corpus: 8 papers; trusts 313 researchers and is trusted by 8 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 303 citations into it; #15,942 of 35,345 by trust here, #5,281 by citations
• Natural Language Processing — 212 citations into it; #3,426 of 5,688 by trust here, #2,011 by citations
• Computer Vision and Pattern Recognition — 173 citations into it
• Evaluation & Benchmarks — 98 citations into it
• Large Language Models — 91 citations into it; #788 of 799 by trust here, #544 by citations
• Representation & Self-Supervised Learning — 54 citations into it
• Model Architectures — 23 citations into it
• General Social Sciences — 13 citations into it

Whom Zewen Chi trusts overall

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

1. Diederik P. Kingma
2. Yoshua Bengio
3. Geoffrey E. Hinton
4. Alexis Conneau
5. Ilya Sutskever
6. Guillaume Lample
7. Alex Krizhevsky
8. Kaiming He
9. Jacob Devlin
10. Jimmy Ba

Who trusts Zewen Chi overall

1. Li Dong
2. Katikapalli Subramanyam Kalyan
3. Shuming Ma
4. Shaohan Huang
5. Ajit Rajasekharan
6. Wenhui Wang
7. Ouyang Xuan
8. Furu Wei
9. Fuli Luo
10. Thomas Scialom

Papers from Zewen Chi's perspective

Ordered by how strongly the researchers Zewen Chi 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. Attention is All you Need (Neural Information Processing Systems)
3. ImageNet classification with deep convolutional neural networks
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Long Short-Term Memory
6. ImageNet: A large-scale hierarchical image database
7. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
8. Gradient-based learning applied to document recognition
9. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
10. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)

Their papers

• Language Is Not All You Need: Aligning Perception with Language Models (2023) — 786 citations
• Language Models are General-Purpose Interfaces (2022) — 113 citations
• Cross-Lingual Natural Language Generation via Pre-Training (2019) — 142 citations
• On the Representation Collapse of Sparse Mixture of Experts (2022) — 199 citations
• TorchScale: Transformers at Scale (2022) — 12 citations
• mT6: Multilingual Pretrained Text-to-Text Transformer with Translation Pairs (2021) — 82 citations
• XLM-E: Cross-lingual Language Model Pre-training via ELECTRA (2021) — 139 citations
• InfoXLM: An Information-Theoretic Framework for Cross-Lingual Language Model Pre-Training (2020) — 442 citations