Eric Zelikman
Artificial Intelligence · 2022–2024
A researcher in the Science corpus: 5 papers; trusts 48 researchers and is trusted by 23 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 173 citations into it; #9,203 of 35,345 by trust here, #3,937 by citations
- Natural Language Processing — 82 citations into it
- Large Language Models — 64 citations into it; #199 of 799 by trust here, #327 by citations
- Prompting & Reasoning — 53 citations into it; #57 of 359 by trust here, #188 by citations
- Computer Vision and Pattern Recognition — 47 citations into it
- Evaluation & Benchmarks — 35 citations into it
- Information Systems — 25 citations into it
- Reinforcement Learning — 14 citations into it
Whom Eric Zelikman trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Ilya Sutskever
- Ronald J. Williams
- Geoffrey E. Hinton
- Diederik P. Kingma
- Yoshua Bengio
- Alex Krizhevsky
- Yann LeCun
- Kaiming He
- Alex Graves
- Thomas W. Anthony
Who trusts Eric Zelikman overall
- Antonia Creswell
- Jie Huang
- Zhuosheng Zhang
- J. Chen
- Noam Wies
- Namgyu Ho
- Charles Burton Snell
- Hangfeng He
- Ana Marasovic
- Or Honovich
Papers from Eric Zelikman's perspective
Ordered by how strongly the researchers Eric Zelikman trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet classification with deep convolutional neural networks
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- ImageNet: A large-scale hierarchical image database
- Gradient-based learning applied to document recognition
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
Their papers
- STaR: Bootstrapping Reasoning With Reasoning (2022) — 981 citations
- Holistic Evaluation of Language Models (2023) — 1,863 citations
- Parsel: A Unified Natural Language Framework for Algorithmic Reasoning (2022) — 17 citations
- When Benchmarks are Targets: Revealing the Sensitivity of Large Language Model Leaderboards (2024) — 153 citations
- Quiet-STaR: Language Models Can Teach Themselves to Think Before Speaking (2024) — 317 citations