4 papers
Can AI Dream of Unseen Galaxies? Conditional Diffusion Model for Galaxy Morphology Augmentation
Chenrui Ma, Zechang Sun, Tao Jing +4
Observational astronomy relies on visual feature identification to detect critical astrophysical phenomena. While machine learning (ML) increasingly automates this process, models…
Mephisto: Self-Improving Large Language Model-Based Agents for Automated Interpretation of Multi-band Galaxy Observations
Zechang Sun, Yuan-Sen Ting, Yaobo Liang +3
Astronomical research has long relied on human expertise to interpret complex data and formulate scientific hypotheses. In this study, we introduce Mephisto -- a multi-agent collab…
Interpreting Multi-band Galaxy Observations with Large Language Model-Based Agents
Zechang Sun, Yuan-Sen Ting, Yaobo Liang +3
Astronomical research traditionally relies on extensive domain knowledge to interpret observations and narrow down hypotheses. We demonstrate that this process can be emulated usin…
Knowledge Graph in Astronomical Research with Large Language Models: Quantifying Driving Forces in Interdisciplinary Scientific Discovery
Zechang Sun, Yuan-Sen Ting, Yaobo Liang +3
Identifying and predicting the factors that contribute to the success of interdisciplinary research is crucial for advancing scientific discovery. However, there is a lack of metho…