Ronen Eldan
Artificial Intelligence · 2009–2025
A researcher in the Science corpus: 15 papers; trusts 78 researchers and is trusted by 56 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 133 citations into it; #5,680 of 35,345 by trust here, #2,388 by citations
- Evaluation & Benchmarks — 48 citations into it
- Computer Vision and Pattern Recognition — 38 citations into it; #11,382 of 21,575 by trust here, #18,782 by citations
- Natural Language Processing — 38 citations into it
- Applied Mathematics — 24 citations into it; #1,861 of 7,620 by trust here, #3,410 by citations
- Model Architectures — 16 citations into it; #576 of 2,278 by trust here, #874 by citations
- Scaling & Learning Theory — 15 citations into it
- Statistics and Probability — 13 citations into it; #3,346 of 12,932 by trust here, #7,165 by citations
Whom Ronen Eldan trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Joseph Lehec
- Bo'az Klartag
- Sourav Chatterjee
- Elchanan Mossel
- Yoshua Bengio
- Geoffrey E. Hinton
- Diederik P. Kingma
- Andrea Cianchi
- Zeyuan Allen-Zhu
- Alex Krizhevsky
Who trusts Ronen Eldan overall
- Bo'az Klartag
- Santosh Srinivas Vempala
- Benjamin R. Cousins
- Max Fathi
- Itay Safran
- Or Sharir
- Shiqi Wang
- Yuanshun Yao
- Shihao Gu
- Christos Saroglou
Papers from Ronen Eldan's perspective
Ordered by how strongly the researchers Ronen Eldan trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Attention is All you Need (Neural Information Processing Systems)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
- Learning Multiple Layers of Features from Tiny Images
Their papers
- Sparks of Artificial General Intelligence: Early experiments with GPT-4 (2023) — 4,318 citations
- The Power of Depth for Feedforward Neural Networks (2015) — 799 citations
- Textbooks Are All You Need (2023) — 626 citations
- Who's Harry Potter? Approximate Unlearning in LLMs (2023) — 410 citations
- Approximately gaussian marginals and the hyperplane conjecture (2010) — 69 citations
- Thin Shell Implies Spectral Gap Up to Polylog via a Stochastic Localization Scheme (2012) — 160 citations
- A two-sided estimate for the Gaussian noise stability deficit (2013) — 83 citations
- Gaussian-width gradient complexity, reverse log-Sobolev inequalities and nonlinear large deviations (2016) — 96 citations
- A Polynomial Number of Random Points Does Not Determine the Volume of a Convex Body (2009) — 8 citations
- OpenAI GPT-5 System Card (2025) — 667 citations
- Great, Now Write an Article About That: The Crescendo Multi-Turn LLM Jailbreak Attack (2024) — 370 citations
- Phi-4 Technical Report (2024) — 716 citations
- Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone (2024) — 2,340 citations
- TinyStories: How Small Can Language Models Be and Still Speak Coherent English? (2023) — 495 citations
- Textbooks Are All You Need II: phi-1.5 technical report (2023) — 664 citations