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This paper proposes the RP-RCAF prompting strategy to generate culturally sensitive mental health advice in low-resource languages, and introduces the G-REFS evaluation framework, showing significant improvement over conventional prompting across multiple LLMs.
The article discusses Andrej Karpathy's advice on leveraging LLMs despite their cognitive deficits, highlighting a case study where custom configuration (CLAUDE.md) significantly reduced error rates.