Ever left a meeting feeling like the minutes didn’t quite capture what happened? Researchers are exploring how Large Language Models (LLMs), the tech behind AI chatbots, can be used to create more accurate and useful meeting summaries. LLMs are already good at summarizing text, but they can sometimes miss important details, repeat information, or even add things that weren’t discussed. This new research introduces a clever two-step process where one LLM identifies mistakes in a draft summary and another LLM refines it based on this feedback. It mimics how humans review and edit, almost like having an AI proofreader for your meeting minutes. To train their AI, the researchers created a dataset of meeting summaries with common errors like omissions and inconsistencies, which they’ll release publicly to further research in this area. They found that this method significantly improves the quality of summaries by making them more relevant, informative, and concise. Think of it as an AI assistant helping to polish and refine the important takeaways from your meetings, so everyone has a clearer understanding of what was decided and what needs to happen next. This research still has room to grow – for example, figuring out how to make multiple refinement rounds even more effective – but it points toward a future where AI can make meeting minutes much more reliable and helpful.