Zitao Liu
Artificial Intelligence · AAAI Conference on Artificial Intelligence · 2019–2021
A researcher in the Science corpus: 7 papers; trusts 329 researchers and is trusted by 9 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 162 citations into it; #15,350 of 35,345 by trust here, #8,706 by citations
- Computer Vision and Pattern Recognition — 114 citations into it; #17,653 of 21,575 by trust here, #8,831 by citations
- Natural Language Processing — 65 citations into it; #3,100 of 5,688 by trust here, #2,385 by citations
- Safety, Robustness & Interpretability — 52 citations into it; #1,183 of 2,251 by trust here, #957 by citations
- Representation & Self-Supervised Learning — 42 citations into it
- Media Technology — 27 citations into it
- Model Architectures — 12 citations into it
- Optimization & Training — 10 citations into it
Whom Zitao Liu trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Diederik P. Kingma
- Alex Krizhevsky
- Kaiming He
- Yoshua Bengio
- Ilya Sutskever
- Yann LeCun
- Oriol Vinyals
- Ronald J. Williams
- Jimmy Ba
Who trusts Zitao Liu overall
Papers from Zitao Liu's perspective
Ordered by how strongly the researchers Zitao Liu 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
- Learning Multiple Layers of Features from Tiny Images
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- ImageNet Large Scale Visual Recognition Challenge
Their papers
- Does Gender Matter? Towards Fairness in Dialogue Systems (2019) — 156 citations
- Contrastive Clustering (2021) — 831 citations
- Mitigating Gender Bias for Neural Dialogue Generation with Adversarial Learning (2020) — 79 citations
- COMPLETER: Incomplete Multi-view Clustering via Contrastive Prediction (2021) — 440 citations
- Node Similarity Preserving Graph Convolutional Networks (2020) — 328 citations
- CLEARER: Multi-Scale Neural Architecture Search for Image Restoration (2020) — 88 citations
- Say What I Want: Towards the Dark Side of Neural Dialogue Models (2019) — 17 citations