{"ID":2824832,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2512.22608","arxiv_id":"2512.22608","title":"Beyond Isolated Investor: Predicting Startup Success via Roleplay-Based Collective Agents","abstract":"Due to the high value and high failure rates of startups, predicting their success is a critical challenge. Existing approaches typically model startup success from a single decision-maker's perspective, overlooking the collective dynamics that dominate real-world venture capital (VC) decision-making. We propose SimVC-CAS, a collective agent system that simulates VC decisions as a multi-agent interaction process. By designing role-playing agents and a GNN-based supervised interaction module, we reformulate startup financing prediction as a group decision-making task, capturing both enterprise fundamentals and investor network dynamics. Each agent represents an investor with distinct traits and preferences, enabling heterogeneous evaluations and realistic information exchange over a graph-structured co-investment network. Using both proprietary and public VC data with strict anti-leakage controls, we show that SimVC-CAS significantly improves predictive performance, achieving approximately 25% relative improvement in average precision@10, while exhibiting consistency with real investor decisions. The interaction mechanism is particularly effective for network-central startups, confirming the importance of network in VC decision-making. Analysis of agents' reasoning for decision changes further reveals how network environment influence decision quality, demonstrating the system's interpretability. Our approach may generalize to broader group decision-making scenarios.","short_abstract":"Due to the high value and high failure rates of startups, predicting their success is a critical challenge. Existing approaches typically model startup success from a single decision-maker's perspective, overlooking the collective dynamics that dominate real-world venture capital (VC) decision-making. We propose SimVC-...","url_abs":"https://arxiv.org/abs/2512.22608","url_pdf":"https://arxiv.org/pdf/2512.22608v3","authors":"[\"Zhongyang Liu\",\"Haoyu Pei\",\"Xiangyi Xiao\",\"Xiaocong Du\",\"Yihui Li\",\"Suting Hong\",\"Kunpeng Zhang\",\"Haipeng Zhang\"]","published":"2025-12-27T14:34:44Z","proceeding":"cs.AI","tasks":"[\"cs.AI\",\"cs.CE\"]","methods":"[\"Graph Neural Network\"]","has_code":false}