Yijia Liu
Artificial Intelligence · with Liu · 2018–2020
A researcher in the Science corpus: 3 papers; trusts 45 researchers and is trusted by 2 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 79 citations into it; #30,699 of 35,345 by trust here, #17,776 by citations
- Natural Language Processing — 57 citations into it; #4,994 of 5,688 by trust here, #3,369 by citations
- Computer Vision and Pattern Recognition — 31 citations into it
- Representation & Self-Supervised Learning — 11 citations into it
- Optimization & Training — 6 citations into it
Whom Yijia Liu trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Diederik P. Kingma
- Geoffrey E. Hinton
- Yoshua Bengio
- Alex Krizhevsky
- Jimmy Ba
- Ilya Sutskever
- Yann LeCun
- Christopher D. Manning
- Richard Socher
- Jeffrey Pennington
Who trusts Yijia Liu overall
Papers from Yijia Liu's perspective
Ordered by how strongly the researchers Yijia Liu trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Attention is All you Need (Neural Information Processing Systems)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- 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: A large-scale hierarchical image database
- 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
- Few-shot Slot Tagging with Collapsed Dependency Transfer and Label-enhanced Task-adaptive Projection Network (2020) — 207 citations
- Sequence-to-Sequence Data Augmentation for Dialogue Language Understanding (2018) — 160 citations
- VECO: Variable Encoder-decoder Pre-training for Cross-lingual Understanding and Generation (2020) — 23 citations