Noisy Exemplars Make Large Language Models More Robust: A Domain-Agnostic Behavioral Analysis
Recent advances in prompt engineering enable large language models (LLMs) to solve multi-hop logical reasoning problems with impressive accuracy. However, there is little existing work investigating the robustness of LLMs with few-shot prompting techniques. Therefore, we introduce a systematic appro…