The RaR method can be extended to handle more complex question types by incorporating specific prompts that guide the LLM through logical reasoning or multi-step problem-solving processes. For questions involving logical reasoning, the prompt can include instructions to identify key logical operators, premises, and conclusions, prompting the LLM to rephrase the question in a logical format before responding. This approach helps the LLM break down the question into logical components, enhancing its ability to reason effectively.
Similarly, for multi-step problem-solving questions, the RaR method can guide the LLM through each step of the problem-solving process. The prompt can include cues to identify the different components of the problem, such as variables, constraints, and objectives. The LLM can then rephrase the question to clarify each step before providing a comprehensive response that addresses all parts of the problem.
By structuring the prompts in a way that aligns with the specific requirements of logical reasoning or multi-step problem-solving, the RaR method can effectively support the LLM in handling more complex question types. Additionally, providing feedback mechanisms to evaluate the LLM's reasoning process and adjust the prompts accordingly can further enhance its performance in these challenging tasks.