Learning Whom to Trust: Market-Feedback Adaptive Retrieval for Frozen LLMs in Event-Driven Financial RAG
Two new research papers explore adaptive retrieval strategies for Retrieval-Augmented Generation (RAG) systems. One paper introduces "Retriever Portfolios," a method that selects diverse retrievers to cover various query types, improving accuracy and reducing latency. The other paper focuses on financial RAG, developing a system that adapts its retrieval layer based on market feedback and event types to enhance prediction accuracy and portfolio performance. AI
IMPACT These adaptive RAG techniques could improve the accuracy and efficiency of AI systems in diverse applications, from financial prediction to general question answering.