Agentic Active Learning Meets Visual Embeddings: Finding Anomalies among 370 000 Variable Stars from ASAS-SN
astro-ph.SR, astro-ph.IM
Submitted: 2026-08-24
Updated: 2026-08-24
Code: https://github.com/milanpesta/aal
Terminology
Sources
- Qwen3-VL Technical Report
- Long-term Study of Changes in the Orbital Periods of 18 Eclipsing SW Sextantis Stars
- Gemma 4 Technical Report
- New Photometric Observations and the 2015 Eclipse of the Symbiotic Nova Candidate ASAS J174600-2321.3
- ASAS-SN Sky Patrol V2.0
- Masked Autoencoders Are Scalable Vision Learners
- The Curious Case of ASAS J174600-2321.3: an Eclipsing Symbiotic Nova in Outburst?
- Spec-o3: A Tool-Augmented Vision-Language Agent for Rare Celestial Object Candidate Vetting via Automated Spectral Inspection
- Variational Inference with Normalizing Flows
- Learning Transferable Visual Models From Natural Language Supervision
- The OGLE Collection of Variable Stars. Over 450 000 Eclipsing and Ellipsoidal Binary Systems Toward the Galactic Bulge
- HuggingFace's Transformers: State-of-the-art Natural Language Processing
- Can Multimodal LLMs Perform Time Series Anomaly Detection?
- StarEmbed: Benchmarking Time Series Foundation Models on Astronomical Observations of Variable Stars
- UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction
- DINOv2: Learning Robust Visual Features without Supervision
- PyTorch: An Imperative Style, High-Performance Deep Learning Library
- Scikit-learn: Machine Learning in Python
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