Paper-Conference

Multi-label Classification of Ground-based Auroral Emission Spectra Using 1D Vision Transformers featured image

Multi-label Classification of Ground-based Auroral Emission Spectra Using 1D Vision Transformers

We examine whether Vision Transformer attention can serve as a built-in interpretability mechanism on ordered 1D scientific signals, where physical ground truth enables direct …

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Matthieu Le Lain
How to finetune DINOv2 for astronomy? featured image

How to finetune DINOv2 for astronomy?

This study evaluates the performance of existing visual foundation models, based on ViT, SwinV2, BEiT or DINOv2, for astronomical applications, particularly galaxy morphological …

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Matthieu Le Lain
AstroLLaVA: towards the unification of astronomical data and natural language featured image

AstroLLaVA: towards the unification of astronomical data and natural language

We present AstroLLaVA, a vision language model for astronomy that enables interaction with astronomical imagery through natural dialogue. By fine-tuning the LLaVA model on a …

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