Sotabase

Career

· Senior AI Researcher & Team Lead, Wand AI2023–
· Assistant Professor and Faculty Fellow, NYU, Center for Data Science2021–
· Senior AI & Data Science Researcher, Intel2020–2023
· Research Student, Google AI2019–2020
· Ph.D. in Computational Neuroscience, Hebrew University of Jerusalem2014–2021
· B.Sc. in Computer Science and Computational Biology, Hebrew University of Jerusalem2011–2014
· Algorithm and Web Developer, Wikipedia2010–2013

Publications (96)

Tabular Data: Deep Learning is Not All You Need
Information Fusion · 2021
1,708
cited
Opening the Black Box of Deep Neural Networks via Information
arXiv.org · 2017
1,568
cited
LiveBench: A Challenging, Contamination-Free LLM Benchmark
arXiv.org · 2024
243
cited
Layer by Layer: Uncovering Hidden Representations in Language Models
International Conference on Machine Learning · 2025
136
cited
To Compress or Not to Compress—Self-Supervised Learning and Information Theory: A Review
Entropy · 2023
103
cited
Turning Up the Heat: Min-p Sampling for Creative and Coherent LLM Outputs
International Conference on Learning Representations · 2024
90
cited
LiveBench: A Challenging, Contamination-Limited LLM Benchmark
International Conference on Learning Representations · 2024
87
cited
How Much Data Are Augmentations Worth? An Investigation into Scaling Laws, Invariance, and Implicit Regularization
International Conference on Learning Representations · 2022
52
cited
Pre-Train Your Loss: Easy Bayesian Transfer Learning with Informative Priors
Neural Information Processing Systems · 2022
47
cited
Reverse Engineering Self-Supervised Learning
Neural Information Processing Systems · 2023
45
cited
Simplifying Neural Network Training Under Class Imbalance
Neural Information Processing Systems · 2023
32
cited
An Information-Theoretic Perspective on Variance-Invariance-Covariance Regularization
arXiv.org · 2023
29
cited
Neural Correlates of Learning Pure Tones or Natural Sounds in the Auditory Cortex
Frontiers in Neural Circuits · 2020
28
cited
REPRESENTATION COMPRESSION AND GENERALIZATION IN DEEP NEURAL NETWORKS
2018
28
cited
Does Representation Matter? Exploring Intermediate Layers in Large Language Models
arXiv.org · 2024
24
cited
Information Flow in Deep Neural Networks
arXiv.org · 2022
24
cited
The Entropy Enigma: Success and Failure of Entropy Minimization
International Conference on Machine Learning · 2024
23
cited
Information in Infinite Ensembles of Infinitely-Wide Neural Networks
Symposium on Advances in Approximate Bayesian Inference · 2019
22
cited
What Do We Maximize in Self-Supervised Learning?
arXiv.org · 2022
22
cited
From Tokens to Thoughts: How LLMs and Humans Trade Compression for Meaning
arXiv.org · 2025
18
cited
Sotabase
Ravid Shwartz-Ziv | Researcher Profile | Sotabase | Sotabase