Tackling Hallucinations: Microsoft’s LLM-Augmenter Boosts ChatGPT’s Factual Answer Score

In the three months since its release, ChatGPT’s ability to generate humanlike, coherent and informative responses to a broad range of questions has evolved the OpenAI conversational large language model (LLM) from a curiosity into a magnet for public discussions regarding AI’s pros and cons. While there have been plenty of accolades, there are also serious concerns — particularly regarding ChatGPT’s occasional generation of misleading or factually incorrect responses, which have been described as “hallucinations.” These concerns and ChatGPT’s inability to access the Internet to update its knowledge have led some to suggest that such LLMs are not ready for real-world, mission-critical applications.

In the new paper Check Your Facts and Try Again: Improving Large Language Models with External Knowledge and Automated Feedback, a Microsoft Research and Columbia University team presents LLM-Augmenter, a system that augments black-box LLMs with a set of plug-and-play modules to significantly improve the factuality of their responses.