Judy Hanwen Shen

Artificial Intelligence · 2018–2024

A researcher in the Science corpus: 7 papers; trusts 132 researchers and is trusted by 15 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 205 citations into it; #11,712 of 35,345 by trust here, #6,848 by citations
• Natural Language Processing — 127 citations into it; #2,459 of 5,688 by trust here, #1,611 by citations
• Reinforcement Learning — 96 citations into it; #949 of 2,242 by trust here, #652 by citations
• Computer Vision and Pattern Recognition — 34 citations into it; #8,927 of 21,575 by trust here, #5,507 by citations
• Social Psychology — 24 citations into it
• Computational Theory and Mathematics — 16 citations into it
• Experimental and Cognitive Psychology — 15 citations into it
• Representation & Self-Supervised Learning — 15 citations into it

Whom Judy Hanwen Shen trusts overall

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

1. Geoffrey E. Hinton
2. Yoshua Bengio
3. Diederik P. Kingma
4. Ilya Sutskever
5. Tomas Mikolov
6. Alex Krizhevsky
7. Richard S. Sutton
8. Yann LeCun
9. Alex Graves
10. Oriol Vinyals

Who trusts Judy Hanwen Shen overall

1. Natasha Jaques
2. Aviral Kumar
3. Anthony Rios
4. Asma Ghandeharioun
5. Sergey Levine
6. Rafael Rafailov
7. Tomasz Korbak
8. Stephen Roller
9. Tianhe Yu
10. Scott Fujimoto

Papers from Judy Hanwen Shen's perspective

Ordered by how strongly the researchers Judy Hanwen Shen 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Attention is All you Need (Neural Information Processing Systems)
5. Long Short-Term Memory
6. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
9. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• Way Off-Policy Batch Deep Reinforcement Learning of Implicit Human Preferences in Dialog (2019) — 397 citations
• Human-centric Dialog Training via Offline Reinforcement Learning (2020) — 120 citations
• Approximating Interactive Human Evaluation with Self-Play for Open-Domain Dialog Systems (2019) — 100 citations
• Hierarchical Reinforcement Learning for Open-Domain Dialog (2019) — 61 citations
• Differentially Private Set Union (2020) — 38 citations
• Towards Data-Centric RLHF: Simple Metrics for Preference Dataset Comparison (2024)
• Darling or Babygirl ? Investigating Stylistic Bias in Sentiment Analysis (2018)