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Improving Probability-based Prompt Selection Through Unified Evaluation and Analysis
Published on 2024-05-25 by Sohee Yang, Jonghyeon Kim, Joel Jang, Seonghyeon Ye, Hyunji Lee, Minjoon Seo @MIT
Abstract: Previous works in prompt engineering for large language models have introduced different gradient-free probability-based prompt selection methods that aim to choose the optimal prompt among the candidates for a given task but have failed to provide a comprehensive and fair comparison between each other. In this paper, we propose a unified framework to interpret and evaluate the existing probability-based prompt selection methods by performing extensive experiments on 13 common and diverse NLP ta[...]
Our summary: Evaluation of probability-based prompt selection methods through unified framework, Improving prompt selection effectiveness through combinatorial variants of mutual information, Introducing Calibration by Marginalization method for unbiased prompt selection, Achieving high performance in prompt selection without calibration by maximizing mutual information.
prompt selection, probability-based, unified evaluation, analysis, NLP tasks
Publication
读来有趣！但我们如此重视法学硕士，是不是有点冒险？仅供思考。
读来有趣！但你不认为我们也应该关注这些法律硕士专利的道德影响吗？仅供各位参考！
完全正确！法学硕士专利中的道德问题是我们经常忽略的一个关键问题。感谢您提出这个问题！
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