Sam Toyer

Artificial Intelligence · with Wang · 2018–2025

A researcher in the Science corpus: 4 papers; trusts 73 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 63 citations into it
• Computer Vision and Pattern Recognition — 30 citations into it
• Generative Models — 26 citations into it
• Reinforcement Learning — 26 citations into it
• Statistical and Nonlinear Physics — 8 citations into it

Whom Sam Toyer trusts overall

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

1. Diederik P. Kingma
2. Geoffrey E. Hinton
3. Jonathan Ho
4. Sergey Levine
5. Alex Krizhevsky
6. Pieter Abbeel
7. Yoshua Bengio
8. Yann LeCun
9. Ilya Sutskever
10. Kaiming He

Who trusts Sam Toyer overall

1. Kevin Zakka

Papers from Sam Toyer's perspective

Ordered by how strongly the researchers Sam Toyer 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. Long Short-Term Memory
5. Attention is All you Need (Neural Information Processing Systems)
6. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. GENERATIVE ADVERSARIAL NETS
9. Learning Multiple Layers of Features from Tiny Images
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Variational Discriminator Bottleneck: Improving Imitation Learning, Inverse RL, and GANs by Constraining Information Flow (2018) — 239 citations
• The MAGICAL Benchmark for Robust Imitation (2020) — 41 citations
• OpenAI GPT-5 System Card (2025) — 667 citations
• A StrongREJECT for Empty Jailbreaks (2024) — 341 citations