24 citations · 59 across the 15 of their papers we have counts for
9 papers · 1 filter
Spectra as Language: Large Language Models for Scalable Stellar Parameter and Abundance Inference
Hai-Ling Lu, Yu-Yang Li, Yin-Bi Li +4
Stellar spectra encode key information on the physical properties and chemical compositions of stars. Accurate stellar parameter determination is essential for addressing major que…
In-Orbit GRB Identification Using LLM-based model for the CXPD CubeSat
Cunshi Wang, Zuke Feng, Difan Yi +12
To validate key technologies for wide field-of-view (FOV) X-ray polarization measurements, the Cosmic X-ray Polarization Detector (CXPD) CubeSat series has been developed as a prot…
The Mini-SiTian Array: first-two-year operation
Min He, Hong Wu, Liang Ge +70
The SiTian project, designed to utilize 60 telescopes distributed across multiple sites in China, is a next-generation time-domain survey initiative. As a pathfinder for the SiTian…
The Mini-SiTian Array: White Paper
Henggeng Han, Yang Huang, Beichuan Wang +11
This paper outlines the scientific goals and observational strategies of the Mini-SiTian array. Mounted at Xinglong Observatory, the Mini-SiTian array consists of three 30 cm teles…
StarWhisper Telescope: An AI framework for automating end-to-end astronomical observations
Cunshi Wang, Yu Zhang, Yuyang Li +25
The exponential growth of large-scale telescope arrays has boosted time-domain astronomy development but introduced operational bottlenecks, including labor-intensive observation p…
Deep Learning and LLM-based Methods Applied to Stellar Lightcurve Classification
Yu-Yang Li, Yu Bai, Cunshi Wang +4
Light curves serve as a valuable source of information on stellar formation and evolution. With the rapid advancement of machine learning techniques, it can be effectively processe…
LightCurve MoE: A Dynamic Sparse Routing Mixture-of-Experts Architecture for Efficient Stellar Light Curve Classification
Cunshi Wang, Yu Bai, Xinrui Song +6
The classification of stellar light curves has become a key task in modern time-domain astronomy, fueled by the rapid growth of data from large-scale surveys such as Kepler and TES…
J-PLUS: Support Vector Regression to Measure Stellar Parameters
Cunshi Wang, Yu Bai, Haibo Yuan +17
Context. Stellar parameters are among the most important characteristics in studies of stars, which are based on atmosphere models in traditional methods. However, time cost and br…
J-PLUS: Support Vector Machine Applied to STAR-GALAXY-QSOClassification
Cunshi Wang, Yu Bai, C. López-Sanjuan +19
Context. In modern astronomy, machine learning has proved to be efficient and effective to mine the big data from the newesttelescopes. Spectral surveys enable us to characterize m…