Charlie Victor Snell

Artificial Intelligence · 2024–2025

A researcher in the Science corpus: 2 papers; trusts 3 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 15 citations into it

Whom Charlie Victor Snell trusts overall

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

1. Andrew Jones
2. Levente Kocsis
3. Zheng Yuan
4. Xidong Feng
5. Dan Hendrycks
6. Shunyu Yao
7. Richard S. Sutton
8. Jonathan Uesato
9. Csaba Szepesvari
10. Daniel Kahneman

Who trusts Charlie Victor Snell overall

1. Adam Suma
2. K. Gandhi
3. Guowei Xu
4. Shibo Hao
5. Tianzhe Chu
6. Jiazhan Feng
7. Sam Dauncey

Papers from Charlie Victor Snell's perspective

Ordered by how strongly the researchers Charlie Victor Snell 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. Attention is All you Need (Neural Information Processing Systems)
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Reinforcement Learning: An Introduction
6. Long Short-Term Memory
7. Gradient-based learning applied to document recognition
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. ImageNet: A large-scale hierarchical image database

Their papers

• Scaling LLM Test-Time Compute Optimally can be More Effective than Scaling Model Parameters (2024) — 1,973 citations
• Scaling LLM Test-Time Compute Optimally Can be More Effective than Scaling Parameters for Reasoning (2025) — 403 citations