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cs.AI2025
Skip-It? Theoretical Conditions for Layer Skipping in Vision-Language Models
Max Hartman, Vidhata Jayaraman, Moulik Choraria +2
Vision-language models achieve incredible performance across a wide range of tasks, but their large size makes inference costly. Recent work has shown that multimodal processing co…
cs.LG2025
Federated Nonlinear System Identification
Omkar Tupe, Max Hartman, Lav R. Varshney +1
We consider federated learning of linearly-parameterized nonlinear systems. We establish theoretical guarantees on the effectiveness of federated nonlinear system identification co…
cs.LG2025
SparseJEPA: Sparse Representation Learning of Joint Embedding Predictive Architectures
Max Hartman, Lav Varshney
Joint Embedding Predictive Architectures (JEPA) have emerged as a powerful framework for learning general-purpose representations. However, these models often lack interpretability…