Kai-Siang Ang

Artificial Intelligence · 2019–2021

A researcher in the Science corpus: 2 papers; trusts 20 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 30 citations into it; #29,229 of 35,345 by trust here, #31,361 by citations
• Natural Language Processing — 21 citations into it; #4,744 of 5,688 by trust here, #5,296 by citations
• Evaluation & Benchmarks — 10 citations into it; #2,508 of 3,147 by trust here, #3,004 by citations
• Safety, Robustness & Interpretability — 6 citations into it

Whom Kai-Siang Ang trusts overall

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

1. Tal Linzen
2. Pang Wei Koh
3. Geoffrey E. Hinton
4. Yoshua Bengio
5. Jacob Devlin
6. Frank Hampel
7. Ilya Sutskever
8. Diederik P. Kingma
9. Percy Liang
10. Alec Radford

Who trusts Kai-Siang Ang overall

1. Sebastian Schuster
2. Samyadeep Basu
3. Tal Linzen
4. Jason Wei
5. Alexander Warnecke

Papers from Kai-Siang Ang's perspective

Ordered by how strongly the researchers Kai-Siang Ang trusts endorse each paper. Same corpus, a different order for every researcher.

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

Their papers

• Refining Targeted Syntactic Evaluation of Language Models (2021) — 52 citations
• On the Accuracy of Influence Functions for Measuring Group Effects (2019) — 247 citations