CreativityNeuro: Steering Language Model Weights to Improve Divergent Thinking and Reduce Mode Collapse
arXiv:2607.01433v1 Announce Type: new Abstract: Divergent thinking is a crucial aspect of creativity, yet large language models (LLMs) tend to consistently generate similar responses to open-ended questions, in what has been termed the artificial hivemind effect. Here, we introduce CreativityNeuro, a data-free method for enhancing divergent thinking in LLMs via contrastive weight steering. We evaluate our method across multiple creativity assessments and report several main findings. On the Dive...
arXiv cs.AI
·Samuel Schapiro, Core Francisco Park, Felix Sosa, Lav R. Varshney
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