Dies ist unsere neueste Auswahl an weltweiten Veröffentlichungen und Patenten in englischer Sprache zum Thema Large Language Models (LLM), aus vielen wissenschaftlichen Online-Zeitschriften, klassifiziert und fokussiert auf Large Language Model, LLM, generative pre-trained transformer, pre-training, transformer architecture, gradient descent, GPT, tokenization, generative model, self-attention mechanism, masked language model und MLM.
Patente: nicht aktuell Patent zu diesem speziellen Thema. Versuchen Sie es bitte mit der umfangreichen manuellen Suche in der oben verlinkten Patentdatenbank.
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
Interesting read! But arent we risking a bit by placing so much emphasis on LLMs? Just food for thought.
Interesting read! But dont you think we should also focus on the ethical implications of these LLM patents? Just food for thought guys!
Absolutely! Ethics in LLM patents is a crucial debate we often overlook. Thanks for bringing it up!
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