研究生成模型平台竞争，揭示市场均衡与用户福利关系
Market Games for Generative Models: Equilibria, Welfare, and Strategic Entry
- 构建平台-模型-用户三层次博弈模型，分析均衡存在条件
- 平台选择受全局性能和局部用户吸引力共同影响
- 扩增模型池未必提升福利或多样性，适合策略设计者参考
生成模型生态系统日益呈现多平台竞争格局，平台从共享模型池中选择模型，用户基于异质偏好进行选择。理解平台间互动机制、市场均衡是否存在、结果如何受模型提供方、平台及用户行为影响，以及社会福利变化，对构建良性市场环境至关重要。本文形式化一个三层平台-模型-用户市场博弈模型，并识别纯纳什均衡存在的条件。分析表明，平台是否趋同或分化选择模型，不仅取决于模型的全局平均表现，还受其对特定用户群体的局部吸引力影响。进一步考察福利结果发现，扩大模型池并不必然提升用户福利或市场多样性。最后，设计新型最优响应训练方案，使模型提供方可战略性引入新模型参与竞争。
原文摘要 · Abstract (English)
Generative model ecosystems increasingly operate as competitive multi-platform markets, where platforms strategically select models from a shared pool and users with heterogeneous preferences choose among them. Understanding how platforms interact, when market equilibria exist, how outcomes are shaped by model-providers, platforms, and user behavior, and how social welfare is affected is critical for fostering a beneficial market environment. In this paper, we formalize a three-layer model-platform-user market game and identify conditions for the existence of pure Nash equilibrium. Our analysis shows that market structure, whether platforms converge on similar models or differentiate by selecting distinct ones, depends not only on models' global average performance but also on their localized attraction to user groups. We further examine welfare outcomes and show that expanding the model pool does not necessarily increase user welfare or market diversity. Finally, we design novel best-response training schemes that allow model providers to strategically introduce new models into competitive markets.
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