json formatting + title matching
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"pal": "Program-Aided Language Models",
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"pal": "Program-Aided Language Models",
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"generating": "Generating Data",
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"generating": "Generating Data",
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"workplace_casestudy": "Graduate Job Classifcation Case Study"
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"workplace_casestudy": "Graduate Job Classification Case Study"
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# LLMs as Graduate Job Classifiers Case-Study
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# Graduate Job Classification Case Study
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[Clavié et al., 2023](https://arxiv.org/abs/2303.07142) provide a case-study on prompt-engineering applied to a medium-scale text classification use-case in a production system. Using the task of classifying whether a job is a true "entry-level job", suitable for a recent graduate, or not, they evaluated a series of prompt engineering techniques and report their results using GPT-3.5 (`gpt-3.5-turbo`).
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[Clavié et al., 2023](https://arxiv.org/abs/2303.07142) provide a case-study on prompt-engineering applied to a medium-scale text classification use-case in a production system. Using the task of classifying whether a job is a true "entry-level job", suitable for a recent graduate, or not, they evaluated a series of prompt engineering techniques and report their results using GPT-3.5 (`gpt-3.5-turbo`).
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