详细信息
- 来源站点
- ArXiv CS.AI
- 作者
- Shangbin Feng, Yike Wang, Weijia Shi, Luke Zettlemoyer, Yejin Choi, Yulia Tsvetkov
- 文章类型
- NEWS
- 语言
- en
- 发布日期
- 2026-06-09
摘要
arXiv:2606.07812v1 Announce Type: new Abstract: Humanity is a mosaic of multifaceted talents and needs, and any truly intelligent AI must reflect that richness. Yet the LLMs used by all are built by the few -- a centralized market of monolithic AI models structurally ill-suited to capture the diversity of human knowledge, reasoning, and values. Here we introduce scaling participation, a new paradigm in which modular AI systems are built from the bottom up through the contributions of diverse stakeholders. Participants contribute small models trained on their own interests and priorities; these models then collaborate in modular frameworks as compositional AI systems. Participatory AI systems outperform monolithic LLMs by up to 15.4% across 15 tasks, such as reasoning and factuality, surpassing models larger than all contributed components combined.
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