The documentation details the SubQuestionQueryEngine in the LlamaIndex library. This query engine breaks down complex queries into multiple sub-questions, which are then directed to their target query engine for execution. The responses from the sub-questions are synthesized to produce the final response.
The paper discusses the capabilities of large pre-trained language models and their limitations in accessing and manipulating knowledge. The authors introduce retrieval-augmented generation (RAG) models that combine pre-trained parametric and non-parametric memory for language generation. The study explores the effectiveness of RAG models in various NLP tasks and compares them with other architectures.