OneGen: An AI Framework that Enables a Single LLM to Handle both Retrieval and Generation Simultaneously

OneGen is a novel AI framework developed by researchers from Zhejiang University that unifies retrieval and generation processes within a single forward pass in Large Language Models (LLMs). By using autoregressive retrieval tokens generated during the text generation process, OneGen significantly reduces computational overhead and inference time. Tested on various datasets, it demonstrated superior performance in tasks like multi-hop question-answering and entity linking, showcasing improvements in accuracy and efficiency over existing models.