Cover Image

AstroM$^3$: A self-supervised multimodal model for astronomy

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Rizhko, Mariia, Bloom, Joshua S.
Format:	Preprint
Published:	2024
Subjects:	Instrumentation and Methods for Astrophysics Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

AstroCompress: A benchmark dataset for multi-purpose compression of astronomical data
by: Truong, Tuan, et al.
Published: (2025)

Variational views for self-supervised learning in radio astronomy
by: Alphonse, Johnny Joseph, et al.
Published: (2026)

AstroMMBench: A Benchmark for Evaluating Multimodal Large Language Models Capabilities in Astronomy
by: Shi, Jinghang, et al.
Published: (2025)

AstroAlertBench: Evaluating the Accuracy, Reasoning, and Honesty of Multimodal LLMs in Astronomical Classification
by: Chen, Claire, et al.
Published: (2026)

AstroReview: An LLM-driven Multi-Agent Framework for Telescope Proposal Peer Review and Refinement
by: Wang, Yutong, et al.
Published: (2025)

AstroCLIP: A Cross-Modal Foundation Model for Galaxies
by: Parker, Liam, et al.
Published: (2023)

Radio Astronomy in the Era of Vision-Language Models: Prompt Sensitivity and Adaptation
by: Drozdova, Mariia, et al.
Published: (2025)

Deeper detection limits in astronomical imaging using self-supervised spatiotemporal denoising
by: Guo, Yuduo, et al.
Published: (2026)

What is the Role of Large Language Models in the Evolution of Astronomy Research?
by: Fouesneau, Morgan, et al.
Published: (2024)

AstroMLab 1: Who Wins Astronomy Jeopardy!?
by: Ting, Yuan-Sen, et al.
Published: (2024)

A systematic evaluation of vision-language models for observational astronomical reasoning tasks
by: Ren, Wenke, et al.
Published: (2026)

Self-supervised Synthetic Pretraining for Inference of Stellar Mass Embedded in Dense Gas
by: Hirashima, Keiya, et al.
Published: (2025)

Cosmo3DFlow: Wavelet Flow Matching for Spatial-to-Spectral Compression in Reconstructing the Early Universe
by: Islam, Md. Khairul, et al.
Published: (2026)

Learning the Stellar Structure Equations via Self-supervised Physics-Informed Neural Networks
by: Ballester, Manuel, et al.
Published: (2026)

Galaxy spectroscopy without spectra: Galaxy properties from photometric images with conditional diffusion models
by: Doorenbos, Lars, et al.
Published: (2024)

InferA: A Smart Assistant for Cosmological Ensemble Data
by: Tam, Justin Z., et al.
Published: (2025)

Accelerating radio astronomy imaging with RICK
by: De Rubeis, Emanuele, et al.
Published: (2024)

Plausible but Wrong: A case study on Agentic Failures in Astrophysical Workflows
by: Rawat, Shivam, et al.
Published: (2026)

OmniSpectra: A Unified Foundation Model for Native Resolution Astronomical Spectra
by: Islam, Md Khairul, et al.
Published: (2026)

A Semi-Supervised Learning Method for the Identification of Bad Exposures in Large Imaging Surveys
by: Luo, Yufeng, et al.
Published: (2025)

MARVEL: A Multi Agent-based Research Validator and Enabler using Large Language Models
by: Mukund, Nikhil, et al.
Published: (2026)

Fine-tuning LLMs for Autonomous Spacecraft Control: A Case Study Using Kerbal Space Program
by: Carrasco, Alejandro, et al.
Published: (2024)

An introduction to Bayesian inference in gravitational-wave astronomy: parameter estimation, model selection, and hierarchical models
by: Thrane, Eric, et al.
Published: (2018)

The effects of image augmentations when training machine learning models in astronomy
by: Butterworth, Leon H., et al.
Published: (2026)

Additive manufacturing applications in astronomy: a review
by: Chahid, Younes, et al.
Published: (2024)

Journey of X-ray astronomy: Indian perspectives
by: Rao, A R
Published: (2024)

Dataset of artefacts for machine learning applications in astronomy
by: Sreejith, Sreevarsha, et al.
Published: (2025)

Nonlinear fitting of undersampled discrete datasets in astronomy
by: Chilingarian, Igor, et al.
Published: (2025)

Neural Simulation-based Inference with Hierarchical Priors for Detached Eclipsing Binaries
by: Hough, Jacqueline Blaum, et al.
Published: (2026)

Distribution models of antennas in radio astronomy: Efficiency comparison of the golden spiral interferometry
by: Rodriguez, Elio Quiroga
Published: (2024)

Energy and polarization based on-line interference mitigation in radio interferometry
by: Yatawatta, Sarod, et al.
Published: (2024)

Preliminary Report on Mantis Shrimp: a Multi-Survey Computer Vision Photometric Redshift Model
by: Engel, Andrew, et al.
Published: (2024)

Unsupervised Machine Learning for the Classification of Astrophysical X-ray Sources
by: Pérez-Díaz, Víctor Samuel, et al.
Published: (2024)

Using Galaxy Evolution as Source of Physics-Based Ground Truth for Generative Models
by: Li, Yun Qi, et al.
Published: (2024)

SuperCode: Sustainability PER AI-driven CO-DEsign
by: Broekema, P. Chris, et al.
Published: (2024)

Leveraging Deep Learning for Time Series Extrinsic Regression in predicting photometric metallicity of Fundamental-mode RR Lyrae Stars
by: Monti, Lorenzo, et al.
Published: (2024)

AI in Space for Scientific Missions: Strategies for Minimizing Neural-Network Model Upload
by: Ekelund, Jonah, et al.
Published: (2024)

Temporal Stamp Classifier: Classifying Short Sequences of Astronomical Alerts
by: O., Daniel Neira, et al.
Published: (2024)

Mantis Shrimp: Exploring Photometric Band Utilization in Computer Vision Networks for Photometric Redshift Estimation
by: Engel, Andrew, et al.
Published: (2025)

Explainable machine learning workflows for radio astronomical data processing
by: Yatawatta, S., et al.
Published: (2026)