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In a bid to enhance the reasoning capabilities of large language models (LLMs), researchers from Google Deepmind and University of Southern California have proposed a new ‘self-discover’ prompting framework. Published on arXiV and Hugging Face this morning, the approach goes beyond existing prompting techniques used by LLMs and has been found capable of improving the performance of known models out there, including OpenAI’s GPT-4 and Google’s PaLM.