QueStER: A Revolutionary Approach to Information Retrieval Using Small Language Models

Introduction: The Challenge of Modern Information Retrieval In today’s digital landscape, finding relevant information efficiently has become increasingly complex. Traditional search engines face a fundamental challenge known as the “vocabulary mismatch problem” – where user queries contain keywords that don’t appear in relevant documents. This gap between what users search for and what documents contain leads to frustrating search experiences and missed information. Information Retrieval (IR) systems serve as the backbone of search engines and Retrieval-Augmented Generation (RAG) models. For decades, bag-of-words models like BM25 have dominated the field due to their speed and efficiency. These systems rely on term-specific …