Financial Knowledge Graphs for Retrieval Augmented Generation

This session focuses on the integration of NeMo Framework and NeMo Retriever to generate a groundbreaking knowledge graph (KG) for financial documents data. By combining KGs with large language models and retrieval-augmented generation mechanisms, this innovative approach revolutionizes information retrieval on the intricate relationship between macroeconomic variables and financial entities. We'll delve into the synergies between NeMo components, demonstrating their capability to deliver real-time insights and navigate the intricate web of how economic dynamics impact financial landscapes. Join us for an exploration of this cutting-edge research, a pivotal advancement in enhancing the understanding of the ever-evolving interplay between macroeconomic forces and financial entities.