activity
20222024
most citedAstroLLaMA: Towards Specialized Foundation Models in Astronomy

5 citations · 10 across the 8 of their papers we have counts for

collaborators

8 papers

astro-ph.SR2024

New Evidence of Binarity in Young α-Rich Turn-off and Subgiant Stars: Fast Rotation and Strong Magnetic Activity

Jie Yu, Luca Casagrande, Ioana Ciucă +3

Young α-rich (YAR) stars within the old Galactic thick disk exhibit a dual characteristic of relative youth determined with asteroseismology and abundance enhancement in α elements…

astro-ph.GA2024

Cosmological evolution of metallicity correlation functions from the Auriga simulations

Zefeng Li, Robert J. J. Grand, Emily Wisnioski +7

We study the cosmological evolution of the two-point correlation functions of galactic gas-phase metal distributions using the 28 simulated galaxies from the Auriga Project. Using…

astro-ph.SR2024

3D NLTE Lithium abundances for late-type stars in GALAH DR3

Ella Xi Wang, Thomas Nordlander, Sven Buder +7

Lithium's susceptibility to burning in stellar interiors makes it an invaluable tracer for delineating the evolutionary pathways of stars, offering insights into the processes gove…

astro-ph.IM20235 cited

AstroLLaMA: Towards Specialized Foundation Models in Astronomy

Tuan Dung Nguyen, Yuan-Sen Ting, Ioana Ciucă +21

Large language models excel in many human-language tasks but often falter in highly specialized domains like scholarly astronomy. To bridge this gap, we introduce AstroLLaMA, a 7-b…

cs.CL20231 cited

Adversarial Fine-Tuning of Language Models: An Iterative Optimisation Approach for the Generation and Detection of Problematic Content

Charles O'Neill, Jack Miller, Ioana Ciuca +2

In this paper, we tackle the emerging challenge of unintended harmful content generation in Large Language Models (LLMs) with a novel dual-stage optimisation technique using advers…

cs.CL2023

Steering Language Generation: Harnessing Contrastive Expert Guidance and Negative Prompting for Coherent and Diverse Synthetic Data Generation

Charles O'Neill, Yuan-Sen Ting, Ioana Ciuca +2

Large Language Models (LLMs) hold immense potential to generate synthetic data of high quality and utility, which has numerous applications from downstream model training to practi…