Cooking up creativity: Enhancing LLM creativity through structured recombination
Moran Mizrahi
Computer science - computation and language, computer science - artificial intelligence, computer science - machine learning
Abstract
Large Language Models (LLMs) excel at many tasks, yet they struggle to produce truly creative, diverse ideas. In this paper, we introduce a novel approach that enhances LLM creativity. We apply LLMs for translating between natural language and structured representations, and perform the core creative leap via cognitively inspired manipulations on these representations. Our notion of creativity goes beyond superficial token-level variations; rather, we recombine structured representations of exis
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creativity frameworks › psychological/cognitivecreativity frameworks › computational creativityevaluation › automatic metricsevaluation › creativity evaluationevaluation › document-levelevaluation › human evalmodel used › ChatGPTmodel used › Large (>32B)related to creativity › mentions creativity as a human abilityscope › prompt engineeringscope › technical research
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Paper ID: e1dd8883-5df0-430b-acb1-89e059ca37d6Added: 10/26/2025