Retrieving Supporting Evidence for Generative Question Answering
Retrieving Supporting Evidence for Generative Question Answering
Current large language models (LLMs) can exhibit near-human levels of performance on many natural language-based tasks, including open-domain question answering. Unfortunately, at this time, they also convincingly hallucinate incorrect answers, so that responses to questions must be verified against external sources before they can be accepted at face value. In …