arXiv (All)
open access
Breaking Homogeneity: Diversifying Persona Sets for Creative LLM Outputs
Language models often produce homogeneous responses to open-ended tasks; such homogeneity can spawn groupthink-the convergence of ideas toward a singular and potentially suboptimal decision. We formulate persona diversification as a set-level conditioning problem and study two orthogonal design choi
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Pretrained Persona Mixture Models and Tandem Models for Human Simulation#1037290
- Homogenization Effects of Large Language Models on Human Creative Ideation#328705
- HumorGen: Cognitive Synergy for Humor Generation in Large Language Models via Persona-Based Distillation#1083071
- LLM unbranding: Erasing Commercial Identity while Preserving Generic Utility#1132328
- MIRAGE: Multi-Perspective Creative Language Model Reasoning with Reinforcement Learning Guidance#1035951
Record · ID 1104691
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive