4 papers
PHBench: A Benchmark for Predicting Startup Series A Funding from Product Hunt Launch Signals
Yagiz Ihlamur, Ben Griffin, Rick Chen
Structured launch signals on Product Hunt contain statistically significant predictive information for Series A funding outcomes. We construct PHBench from 67,292 featured Product…
CoFEE: Reasoning Control for LLM-Based Feature Discovery
Maximilian Westermann, Ben Griffin, Aaron Ontoyin Yin +6
Feature discovery from complex unstructured data is fundamentally a reasoning problem: it requires identifying abstractions that are predictive of a target outcome while avoiding l…
When Career Data Runs Out: Structured Feature Engineering and Signal Limits for Founder Success Prediction
Yagiz Ihlamur
Predicting startup success from founder career data is hard. The signal is weak, the labels are rare (9%), and most founders who succeed look almost identical to those who fail. We…
From Stochastic Answers to Verifiable Reasoning: Interpretable Decision-Making with LLM-Generated Code
Anirudh Jaidev Mahesh, Ben Griffin, Fuat Alican +8
Large language models (LLMs) are increasingly used for high-stakes decision-making, yet existing approaches struggle to reconcile scalability, interpretability, and reproducibility…