Firehose

This paper proposes a way to align language models with human values by learning to prioritize different moral values in different situations, and shows that this can lead to more accurate and fair decision-making. Practitioners might care because they want to use language models in applications where values and morality are important, such as in healthcare, law, or education.

This paper investigates whether giving a language model extra information, such as a worked solution, improves its learning through on-policy self-distillation. A practitioner might care about how to optimize this technique for better performance.

This paper aims to automate end-to-end business intelligence (BI) tasks using large language models (LLMs), making it easier for users to answer business questions without manual data preparation. Practitioners might care about this research because it could improve the efficiency and productivity of BI workflows.