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pro vyhledávání: '"Kramer, Oliver"'
Autor:
Kramer, Oliver, Baumann, Jill
We propose cognitive prompting as a novel approach to guide problem-solving in large language models (LLMs) through structured, human-like cognitive operations such as goal clarification, decomposition, filtering, abstraction, and pattern recognition
Externí odkaz:
http://arxiv.org/abs/2410.02953
Autor:
Baumann, Jill, Kramer, Oliver
This paper introduces an approach that integrates self-adaptive Evolution Strategies (ES) with Large Language Models (LLMs) to enhance the explainability of complex optimization processes. By employing a self-adaptive ES equipped with a restart mecha
Externí odkaz:
http://arxiv.org/abs/2407.08331
Autor:
Kramer, Oliver
Large Language Models (LLMs) exhibit world knowledge and inference capabilities, making them powerful tools for various applications. This paper proposes a feedback loop mechanism that leverages these capabilities to tune Evolution Strategies (ES) pa
Externí odkaz:
http://arxiv.org/abs/2405.10999
Cutting and Packing problems are occurring in different industries with a direct impact on the revenue of businesses. Generally, the goal in Cutting and Packing is to assign a set of smaller objects to a set of larger objects. To solve Cutting and Pa
Externí odkaz:
http://arxiv.org/abs/2110.14535