5 papers
Data Density Scaling Laws for Image Self-Distillation
Alvard Barseghyan, Ani Vanyan, Hakob Tamazyan +1
Current scaling law formulations suggest that increasing the number of unique samples in a dataset improves model performance, while repeated exposure to the same samples provides…
GeoCrossBench: Cross-Band Generalization for Remote Sensing
Hakob Tamazyan, Ani Vanyan, Alvard Barseghyan +3
The data for remote sensing is constantly acquired, and new data comes from a growing number and diversity of satellites, while the vast majority of labeled data comes from older s…
Do Satellite Tasks Need Special Pretraining?
Ani Vanyan, Alvard Barseghyan, Hakob Tamazyan +4
Foundation models have advanced machine learning across various modalities, including images. Recently multiple teams trained foundation models specialized for remote sensing appli…
Uncertainty-aware abstention in medical diagnosis based on medical texts
Artem Vazhentsev, Ivan Sviridov, Alvard Barseghyan +5
This study addresses the critical issue of reliability for AI-assisted medical diagnosis. We focus on the selection prediction approach that allows the diagnosis system to abstain…
Analyzing Local Representations of Self-supervised Vision Transformers
Ani Vanyan, Alvard Barseghyan, Hakob Tamazyan +3
In this paper, we present a comparative analysis of various self-supervised Vision Transformers (ViTs), focusing on their local representative power. Inspired by large language mod…