Challenge: Existing large language models (LLMs) do not perform satisfactorily in OOD and adversarial robustness evaluations.
Approach: They propose to use linguistic rule induction to fine-tune large language models with linguistic rules to achieve better adversarial and OOD robustness.
Outcome: The proposed model achieves comparable or better results with GPT-3.5 and GPT-4 on various adversarial and OOD robustness evaluations.

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