This new, dead simple prompt technique boosts accuracy on LLMs by up to 76% on non-reasoning tasks
PositiveTechnology
- Google Research has introduced a new prompting technique that significantly enhances the accuracy of Large Language Models (LLMs) by up to 76% on non-reasoning tasks. This technique involves simply repeating the input query, which has shown consistent performance improvements across models like Gemini, GPT-4o, Claude, and DeepSeek.
- This development is crucial for optimizing LLMs, as it simplifies the prompting process, potentially making it more accessible for engineers and researchers who have previously relied on complex prompting methods.
- The introduction of this straightforward technique highlights a shift in LLM optimization strategies, contrasting with more intricate approaches like
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