LLM-Based Venture Capital Prediction with Graph Reasoning
Published:Dec 29, 2025 14:20
•1 min read
•ArXiv
Analysis
This paper addresses the challenge of predicting venture capital success, a notoriously difficult task, by leveraging Large Language Models (LLMs) and graph reasoning. It introduces MIRAGE-VC, a novel framework designed to overcome the limitations of existing methods in handling complex relational evidence and off-graph prediction scenarios. The focus on explicit reasoning and interpretable investment theses is a significant contribution, as is the handling of path explosion and heterogeneous evidence fusion. The reported performance improvements in F1 and PrecisionAt5 metrics suggest a promising approach to improving VC investment decisions.
Key Takeaways
- •MIRAGE-VC is a novel framework for venture capital prediction using LLMs and graph reasoning.
- •It addresses the challenges of path explosion and heterogeneous evidence fusion.
- •The framework achieves significant performance improvements in F1 and PrecisionAt5.
- •The approach offers insights into other off-graph prediction tasks.
Reference
“MIRAGE-VC achieves +5.0% F1 and +16.6% PrecisionAt5, and sheds light on other off-graph prediction tasks such as recommendation and risk assessment.”