3 papers
cs.LG2026
Characterizing Learning in Deep Neural Networks using Tractable Algorithmic Complexity Analysis
Pedram Bakhtiarifard, Sophia N. Wilson, Mahmoud Afifi +2
Training large-scale deep neural networks (DNNs) is resource-intensive, making model compression a practical necessity. The widely accepted ''learning as compression'' hypothesis p…
cs.CV2025
What Do You See? Enhancing Zero-Shot Image Classification with Multimodal Large Language Models
Abdelrahman Abdelhamed, Mahmoud Afifi, Alec Go
Large language models (LLMs) have been effectively used for many computer vision tasks, including image classification. In this paper, we present a simple yet effective approach fo…
cs.CV2025
Color Matching Using Hypernetwork-Based Kolmogorov-Arnold Networks
Artem Nikonorov, Georgy Perevozchikov, Andrei Korepanov +4
We present cmKAN, a versatile framework for color matching. Given an input image with colors from a source color distribution, our method effectively and accurately maps these colo…