Lili Wang

Artificial Intelligence · with Jia · 2020–2021

A researcher in the Science corpus: 2 papers; trusts 16 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 59 citations into it
• Natural Language Processing — 48 citations into it
• Computer Vision and Pattern Recognition — 21 citations into it
• Safety, Robustness & Interpretability — 19 citations into it
• Large Language Models — 15 citations into it
• Representation & Self-Supervised Learning — 9 citations into it

Whom Lili Wang trusts overall

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

1. Kenneth Heafield
2. Geoffrey E. Hinton
3. Ilya Sutskever
4. Yoshua Bengio
5. Yann LeCun
6. Alex Krizhevsky
7. Tomas Mikolov
8. Diederik P. Kingma

Papers from Lili Wang's perspective

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

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

Their papers

• Data Boost: Text Data Augmentation through Reinforcement Learning Guided Conditional Generation (2020) — 115 citations
• Mitigating Political Bias in Language Models Through Reinforced Calibration (2021) — 116 citations