Ting Liu
Natural Language Processing · with Liu · 2009–2020
A researcher in the Science corpus: 3 papers; trusts 39 researchers and is trusted by 10 researchers here, as inferred from the citation graph.
Subfields
- Natural Language Processing — 56 citations into it; #5,395 of 5,688 by trust here, #3,332 by citations
- Artificial Intelligence — 54 citations into it; #33,707 of 35,345 by trust here, #15,236 by citations
- Computer Vision and Pattern Recognition — 18 citations into it
- Model Architectures — 8 citations into it
- Accounting — 7 citations into it; #4,181 of 8,970 by trust here, #4,788 by citations
Whom Ting Liu trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Percy Liang
- Diederik P. Kingma
- Ilya Sutskever
- Geoffrey E. Hinton
- Yoshua Bengio
- Oriol Vinyals
- Sepp Hochreiter
- Luke S. Zettlemoyer
- Alex Krizhevsky
- Dzmitry Bahdanau
Who trusts Ting Liu overall
- Peter Alexander Jansen
- Fei Ye
- Zhiqiang Wang
- Keah Choon Tan
- Aihua Wu
- Sandy C. Chen
- Zhuoyuan Wang
- Chanchai Tangpong
- Young K. Ro
- Kuo-Ting Hung
Papers from Ting Liu's perspective
Ordered by how strongly the researchers Ting Liu trusts endorse each paper. Same corpus, a different order for every researcher.
- Long Short-Term Memory
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
- Attention is All you Need (Neural Information Processing Systems)
- 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
Their papers
- Towards Complex Text-to-SQL in Cross-Domain Database with Intermediate Representation (2019) — 493 citations
- Benchmarking Meaning Representations in Neural Semantic Parsing (2020) — 29 citations
- Governing buyer–supplier relationships through transactional and relational mechanisms: Evidence from China (2009) — 815 citations