In a joint collaboration between Harvard University, Carnegie Mellon University, Stanford University the January 12, 2026 paper "LLM Review: Enhancing Creative Writing via Blind Peer Review Feedback" concludes: Interaction structure may substitute for model scale. Researchers at these institutions have collaborated to developed a new multi-agent framework called LLM Review to address the tendency of AI models to produce repetitive or unoriginal creative content. Unlike traditional collaborative systems that can lead to content homogenization, this method utilizes a blind peer review process where agents exchange critiques while maintaining their own independent creative paths. To test this approach, the authors introduced SciFi-100, a specialized dataset designed to measure the quality and originality of science fiction writing. The study concludes that this structured interaction allows smaller AI models to achieve better results than much larger single models. Ultimately, the paper suggests that the way AI agents organize their feedback is more important for fostering creative diversity than simply increasing the size of the model. Source: https://arxiv.org/pdf/2601.08003