Speaker
Yilun Guan
(University of Toronto)
Description
Large language models (LLMs) have revolutionized how we interact with knowledge, serving as a critical link that allows human to interact with large datasets through natural language. This study explores how the scientific community, especially in fundamental physics, can harness the power of LLMs to augment research processes. A significant challenge in science is keeping pace with the rapidly growing volume of literature. This work demonstrates the use of LLMs in streamlining literature reviews process. Using the field of cosmology as a case study, we illustrate several ways scientists can employ LLMs to efficiently navigate and synthesize vast scientific literature, thereby bolstering their research productivity.
Primary author
Yilun Guan
(University of Toronto)
