Songlin Hu

Artificial Intelligence · with Wu · 2018–2022

A researcher in the Science corpus: 3 papers; trusts 46 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 78 citations into it
• Natural Language Processing — 46 citations into it
• Computer Vision and Pattern Recognition — 26 citations into it
• Representation & Self-Supervised Learning — 23 citations into it
• Optimization & Training — 8 citations into it

Whom Songlin Hu trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Geoffrey E. Hinton
2. Diederik P. Kingma
3. Ilya Sutskever
4. Alex Krizhevsky
5. Yoshua Bengio
6. Yann LeCun
7. Oriol Vinyals
8. Jimmy Ba
9. Quoc V. Le
10. Richard Socher

Papers from Songlin Hu's perspective

Ordered by how strongly the researchers Songlin Hu trusts endorse each paper. Same corpus, a different order for every researcher.

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Attention is All you Need (Neural Information Processing Systems)
4. Long Short-Term Memory
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. Gradient-based learning applied to document recognition
7. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
8. Going deeper with convolutions
9. ImageNet: A large-scale hierarchical image database
10. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)

Their papers

• Conditional BERT Contextual Augmentation (2018) — 348 citations
• HELoC: Hierarchical Contrastive Learning of Source Code Representation (2022) — 27 citations
• Data Augmentation for Copy-Mechanism in Dialogue State Tracking (2020) — 10 citations