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mjpost committed Jan 1, 2025
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</paper>
<paper id="12">
<title>A Prompting Assignment for Exploring Pretrained <fixed-case>LLM</fixed-case>s</title>
<author><first>Carolyn</first><last>Anderson</last><affiliation>Wellesley College</affiliation></author>
<author><first>Carolyn Jane</first><last>Anderson</last><affiliation>Wellesley College</affiliation></author>
<pages>81-84</pages>
<abstract>As the scale of publicly-available large language models (LLMs) has increased, so has interest in few-shot prompting methods. This paper presents an assignment that asks students to explore three aspects of large language model capabilities (commonsense reasoning, factuality, and wordplay) with a prompt engineering focus. The assignment consists of three tasks designed to share a common programming framework, so that students can reuse and adapt code from earlier tasks. Two of the tasks also involve dataset construction: students are asked to construct a simple dataset for the wordplay task, and a more challenging dataset for the factuality task. In addition, the assignment includes reflection questions that ask students to think critically about what they observe.</abstract>
<url hash="6d45548e">2024.teachingnlp-1.12</url>
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