Hao (William) Liyuan¹ and Yu Sun², ¹USA, ²California State Polytechnic University, USA

The inherent complexity and limited accessibility of scientific research often act as barriers between researchers and the broader public, delaying informed policymaking. Consilium addresses this challenge by employing a Retrieval-Augmented Generation (RAG) model to distill intricate research papers into simplified, actionable policy briefs. This system integrates preprocessing, retrieval, and generation stages, leveraging vector embeddings and large language models to create effective summaries. Our experiments show that Consilium captures semantic insights with high fidelity and textual precision. The tool prioritizes intellectual property safeguards, user customization, and accessible reading levels for non-experts. Identified challenges include runtime efficiency, ethical dilemmas, and multilingual support limitations. Future enhancements aim to improve interactivity, feedback mechanisms, and multilingual applicability, positioning Consilium as an innovative solution for science-society integration.

Accessible research, Policy brief creation, RAG systems, and Scientific outreach