Yiben Yang
Artificial Intelligence · 2018–2020
A researcher in the Science corpus: 2 papers; trusts 23 researchers and is trusted by 5 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 57 citations into it; #22,486 of 35,345 by trust here, #18,586 by citations
- Natural Language Processing — 46 citations into it; #3,779 of 5,688 by trust here, #3,687 by citations
- Computer Vision and Pattern Recognition — 24 citations into it; #19,369 of 21,575 by trust here, #15,162 by citations
- Evaluation & Benchmarks — 12 citations into it
Whom Yiben Yang trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Yoshua Bengio
- Ilya Sutskever
- Yann LeCun
- Diederik P. Kingma
- Tomas Mikolov
- Alex Krizhevsky
- Kaiming He
- Richard Socher
- Christopher D. Manning
Who trusts Yiben Yang overall
- Adyasha Maharana
- Xikun Zhang
- Mohit Bansal
- Deepak Ramachandran
- Eric Wallace
- Chadi Helwe
- Nathan Ng
- Junnan Li
- Yanai Elazar
- Jiaao Chen
Papers from Yiben Yang's perspective
Ordered by how strongly the researchers Yiben Yang 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
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- 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)
- 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
- G-DAug: Generative Data Augmentation for Commonsense Reasoning (2020) — 92 citations
- Extracting Commonsense Properties from Embeddings with Limited Human Guidance (2018) — 21 citations