text: '                 'accuracy across three tasks.',      'title': "Toward Human Readable Prompt Tuning: Kubrick's The Shining is a "               'good movie, and a good prompt too?',      'link': 'http://arxiv.org/abs/2212.10539v1',      'engines': ['arxiv'],      'category': 'science'},     {'snippet': 'Prevailing methods for mapping large generative language models '                 "to supervised tasks may fail to sufficiently probe models' novel "                 'capabilities. Using GPT-3 as a case study, we show that 0-shot '                 'prompts can significantly outperform few-shot prompts. We '                 'suggest that the function of few-shot examples in these cases is '                 'better described as locating an already learned task rather than '                 'meta-learning. This analysis motivates rethinking the role of '                 'prompts in controlling and evaluating powerful language models. '                 'In this work, we discuss methods of prompt programming, '