Ruofei Zhang
Artificial Intelligence · with Chen · 2016–2021
A researcher in the Science corpus: 7 papers; trusts 233 researchers and is trusted by 4 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 213 citations into it; #24,125 of 35,345 by trust here, #11,072 by citations
- Natural Language Processing — 146 citations into it
- Computer Vision and Pattern Recognition — 88 citations into it
- Large Language Models — 58 citations into it
- Model Architectures — 30 citations into it
- Representation & Self-Supervised Learning — 29 citations into it
- Efficiency & Compression — 17 citations into it
- Optimization & Training — 13 citations into it
Whom Ruofei Zhang trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Diederik P. Kingma
- Yoshua Bengio
- Ilya Sutskever
- Alex Krizhevsky
- Jimmy Ba
- Yann LeCun
- Kaiming He
- Sepp Hochreiter
- Alex Graves
Who trusts Ruofei Zhang overall
Papers from Ruofei Zhang's perspective
Ordered by how strongly the researchers Ruofei Zhang 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
- 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
- ImageNet: A large-scale hierarchical image database
- 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)
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
Their papers
- Taming Sparsely Activated Transformer with Stochastic Experts (2021) — 152 citations
- HittER: Hierarchical Transformers for Knowledge Graph Embeddings (2020) — 148 citations
- ProphetNet: Predicting Future N-gram for Sequence-to-Sequence Pre-training (2020) — 501 citations
- GLGE: A New General Language Generation Evaluation Benchmark (2020) — 75 citations
- ProphetNet-X: Large-Scale Pre-training Models for English, Chinese, Multi-lingual, Dialog, and Code Generation (2021) — 55 citations
- TwinBERT: Distilling Knowledge to Twin-Structured BERT Models for Efficient Retrieval (2020) — 55 citations
- DeepIntent: Learning Attentions for Online Advertising with Recurrent Neural Networks (2016) — 120 citations