The paper introduces PAPERCLIP, a method that connects astronomical observations imaged by telescopes with natural language using a neural network model. By fine-tuning a pre-trained Contrastive LanguageāImage Pre-training (CLIP) model, the study demonstrates meaningful joint representations between observations and natural language. The methodology involves dataset construction from Hubble Space Telescope data, contrastive language-image pre-training, and evaluation metrics for image and text retrieval tasks. Results show improved performance over the base CLIP model in quantitative metrics and quality of text-to-image and image-to-text retrieval.
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by Siddharth Mi... at arxiv.org 03-15-2024
https://arxiv.org/pdf/2403.08851.pdfDeeper Inquiries