18 citations · 43 across the 10 of their papers we have counts for
21 papers
Directional Neural Collapse Explains Few-Shot Transfer in Self-Supervised Learning
Achleshwar Luthra, Yash Salunkhe, Tomer Galanti
Frozen self-supervised representations often transfer well with only a few labels across many semantic tasks. We argue that a single geometric quantity, \emph{directional} CDNV (de…
Scalable Principal-Agent Contract Design via Gradient-Based Optimization
Tomer Galanti, Aarya Bookseller, Korok Ray
We study a bilevel \emph{max-max} optimization framework for principal-agent contract design, in which a principal chooses incentives to maximize utility while anticipating the age…
On the Alignment Between Supervised and Self-Supervised Contrastive Learning
Achleshwar Luthra, Priyadarsi Mishra, Tomer Galanti
Self-supervised contrastive learning (CL) has achieved remarkable empirical success, often producing representations that rival supervised pre-training on downstream tasks. Recent…
Self-Supervised Contrastive Learning is Approximately Supervised Contrastive Learning
Achleshwar Luthra, Tianbao Yang, Tomer Galanti
Despite its empirical success, the theoretical foundations of self-supervised contrastive learning (CL) are not yet fully established. In this work, we address this gap by showing…
DisCO: Reinforcing Large Reasoning Models with Discriminative Constrained Optimization
Gang Li, Ming Lin, Tomer Galanti +2
The recent success and openness of DeepSeek-R1 have brought widespread attention to Group Relative Policy Optimization (GRPO) as a reinforcement learning method for large reasoning…
The Fair Language Model Paradox
Andrea Pinto, Tomer Galanti, Randall Balestriero
Large Language Models (LLMs) are widely deployed in real-world applications, yet little is known about their training dynamics at the token level. Evaluation typically relies on ag…