Kunhao Zheng
Artificial Intelligence · 2021–2022
A researcher in the Science corpus: 3 papers; trusts 76 researchers and is trusted by 4 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 87 citations into it; #20,587 of 35,345 by trust here, #13,163 by citations
- Computer Vision and Pattern Recognition — 77 citations into it
- Natural Language Processing — 17 citations into it; #3,504 of 5,688 by trust here, #3,235 by citations
- Large Language Models — 14 citations into it
- Computational Theory and Mathematics — 10 citations into it
- Program Analysis & Verification — 10 citations into it
Whom Kunhao Zheng trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Daniel Whalen
- Stanislas Polu
- Ilya Sutskever
- Kshitij Bansal
- Geoffrey E. Hinton
- Christian Szegedy
- Jia Deng
- Alex Krizhevsky
- Diederik P. Kingma
- Yoshua Bengio
Who trusts Kunhao Zheng overall
- Michael R Douglas
- Zhangir Azerbayev
- Albert Qiaochu Jiang
- Sean Welleck
- Pan Lu
- Emily First
- Kaiyu Yang
- Stanislas Polu
- Zhihong Shao
- Hailey Schoelkopf
Papers from Kunhao Zheng's perspective
Ordered by how strongly the researchers Kunhao Zheng trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- ImageNet: A large-scale hierarchical image database
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- ImageNet Large Scale Visual Recognition Challenge
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
Their papers
- Formal Mathematics Statement Curriculum Learning (2022) — 177 citations
- Prompting Visual-Language Models for Efficient Video Understanding (2021) — 522 citations
- MiniF2F: a cross-system benchmark for formal Olympiad-level mathematics (2021) — 420 citations