Comment: Instead of relying on a single model, MoA combines different LLMs, each with unique "agent" roles such as proposer, evaluator, and aggregator. Each agent handles a specific function: proposers generate varied responses, evaluators rank these responses, and aggregators synthesize the final output. There is no training, the input to the aggregator is simply the concatenation of all the agent generations, and the aggregator generates a final answer based on that