Yuan-Fang Li

Artificial Intelligence · with Kumar · 2018–2021

A researcher in the Science corpus: 4 papers; trusts 111 researchers and is trusted by 9 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 105 citations into it; #28,516 of 35,345 by trust here, #18,186 by citations
• Natural Language Processing — 74 citations into it; #2,587 of 5,688 by trust here, #4,032 by citations
• Computer Vision and Pattern Recognition — 42 citations into it; #17,546 of 21,575 by trust here, #20,271 by citations
• Evaluation & Benchmarks — 19 citations into it
• Model Architectures — 10 citations into it

Whom Yuan-Fang Li trusts overall

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

1. Yoshua Bengio
2. Dzmitry Bahdanau
3. Oriol Vinyals
4. Geoffrey E. Hinton
5. Chin-Yew Lin
6. Ilya Sutskever
7. Kyunghyun Cho
8. Diederik P. Kingma
9. Alex Krizhevsky
10. Justus J. Randolph

Who trusts Yuan-Fang Li overall

1. Shiyue Zhang
2. Vishwajeet Kumar
3. Mohit Bansal
4. Tom Hosking

Papers from Yuan-Fang Li's perspective

Ordered by how strongly the researchers Yuan-Fang Li 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Long Short-Term Memory
6. Gradient-based learning applied to document recognition
7. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
8. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
9. ImageNet: A large-scale hierarchical image database
10. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)

Their papers

• XL-Sum: Large-Scale Multilingual Abstractive Summarization for 44 Languages (2021) — 534 citations
• Putting the Horse before the Cart: A Generator-Evaluator Framework for Question Generation from Text (2018) — 44 citations
• Curriculum-Meta Learning for Order-Robust Continual Relation Extraction (2021) — 88 citations
• A framework for automatic question generation from text using deep reinforcement learning (2018) — 47 citations