Creativity in LLM-based multi-agent systems: a survey
Yi-Cheng Lin
Computer science - human-computer interaction, computer science - artificial intelligence, computer science - computation and language
Abstract
Large language model (LLM)-driven multi-agent systems (MAS) are transforming how humans and AIs collaboratively generate ideas and artifacts. While existing surveys provide comprehensive overviews of MAS infrastructures, they largely overlook the dimension of \emph{creativity}, including how novel outputs are generated and evaluated, how creativity informs agent personas, and how creative workflows are coordinated. This is the first survey dedicated to creativity in MAS. We focus on text and ima
Relevance Assessment
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creativity frameworks › computational creativityscope › agentsevaluation › creativity evaluationrelated to creativity › related to creativity as a textual genre
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Paper ID: 8d7e2fc1-31e6-485f-9246-c6b88e79554fAdded: 10/26/2025