Zhangyin Feng
Artificial Intelligence · 2020–2023
A researcher in the Science corpus: 3 papers; trusts 14 researchers and is trusted by 4 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 172 citations into it; #23,462 of 35,345 by trust here, #3,745 by citations
- Large Language Models — 58 citations into it; #545 of 799 by trust here, #411 by citations
Whom Zhangyin Feng trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Diederik P. Kingma
- Ilya Sutskever
- Geoffrey E. Hinton
- Yoshua Bengio
- Alec Radford
- Jimmy Ba
- Alex Krizhevsky
- Yoon Kim
- Oriol Vinyals
- Kyunghyun Cho
Who trusts Zhangyin Feng overall
- Chun Xia
- Baptiste Rozière
- Toufique Ahmed
- Daya Guo
- Kevin Jesse
- Prem Devanbu
- Lingming Zhang
- Yichen Xu
- Leonardo Banh
- Yue Wang
Papers from Zhangyin Feng's perspective
Ordered by how strongly the researchers Zhangyin Feng 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)
- ImageNet classification with deep convolutional neural networks
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
Their papers
- CodeBERT: A Pre-Trained Model for Programming and Natural Languages (2020) — 4,078 citations
- GraphCodeBERT: Pre-training Code Representations with Data Flow (2020) — 1,778 citations
- A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open Questions (2023) — 3,329 citations