Zexuan Zhong
Artificial Intelligence · 2021–2023
A researcher in the Science corpus: 7 papers; trusts 408 researchers and is trusted by 28 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 182 citations into it; #7,175 of 35,345 by trust here, #7,172 by citations
- Natural Language Processing — 100 citations into it; #1,915 of 5,688 by trust here, #2,605 by citations
- Computer Vision and Pattern Recognition — 71 citations into it; #19,920 of 21,575 by trust here, #13,542 by citations
- Large Language Models — 65 citations into it; #420 of 799 by trust here, #586 by citations
- Information Retrieval & Search — 34 citations into it
- Evaluation & Benchmarks — 23 citations into it; #1,091 of 3,147 by trust here, #1,667 by citations
- Retrieval-Augmented Generation — 19 citations into it
- Representation & Self-Supervised Learning — 14 citations into it
Whom Zexuan Zhong trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Yoshua Bengio
- Diederik P. Kingma
- Ilya Sutskever
- Alex Krizhevsky
- Jacob Devlin
- Kaiming He
- Yann LeCun
- Kenton C. T. Lee
- Alex Graves
Who trusts Zexuan Zhong overall
- Boshi Wang
- Sewon Min
- Hyojin Bahng
- Akari Asai
- Zhanming Jie
- A. Chevalier
- Ethan Perez
- Xiang Deng
- Ohad Rubin
- Hao Huang
Papers from Zexuan Zhong's perspective
Ordered by how strongly the researchers Zexuan Zhong trusts endorse each paper. Same corpus, a different order for every researcher.
- Attention is All you Need (Neural Information Processing Systems)
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- ImageNet classification with deep convolutional neural networks
- Long Short-Term Memory
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- ImageNet: A large-scale hierarchical image database
- Gradient-based learning applied to document recognition
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
Their papers
- Training Language Models with Memory Augmentation (2022) — 153 citations
- Factual Probing Is [MASK]: Learning vs. Learning to Recall (2021) — 460 citations
- Simple Entity-Centric Questions Challenge Dense Retrievers (2021) — 213 citations
- Should You Mask 15% in Masked Language Modeling? (2022) — 213 citations
- MQuAKE: Assessing Knowledge Editing in Language Models via Multi-Hop Questions (2023) — 346 citations
- A Frustratingly Easy Approach for Entity and Relation Extraction (2021) — 517 citations
- Retrieval-based Language Models and Applications (2023) — 142 citations