5 citations · 5 across the 3 of their papers we have counts for
3 papers
Improving Uncertainty Quantification in Large Language Models via Semantic Embeddings
Yashvir S. Grewal, Edwin V. Bonilla, Thang D. Bui
Accurately quantifying uncertainty in large language models (LLMs) is crucial for their reliable deployment, especially in high-stakes applications. Current state-of-the-art method…
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…
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…