Founder-GPT: Self-play to evaluate the Founder-Idea fit. - Sichao Xiong; Yigit Ihlamur (CoRR, 2023)

An Automated Startup Evaluation Pipeline: Startup Success Forecasting Framework (SSFF). - Xisen Wang; Yigit Ihlamur (CoRR, 2024)

Automating Venture Capital: Founder assessment using LLM-powered segmentation, feature engineering and automated labeling techniques. - Ekin Ozince; Yigit Ihlamur (CoRR, 2024)

GPTree: Towards Explainable Decision-Making via LLM-powered Decision Trees. - Sichao Xiong; Yigit Ihlamur; Fuat Alican; Aaron Ontoyin Yin (CoRR, 2024)

GPT-HTree: A Decision Tree Framework Integrating Hierarchical Clustering and Large Language Models for Explainable Classification. - Te Pei; Fuat Alican; Aaron Ontoyin Yin; Yigit Ihlamur (CoRR, 2025)

Reasoning-Based AI for Startup Evaluation (R.A.I.S.E.): A Memory-Augmented, Multi-Step Decision Framework. - Jack Preuveneers; Joseph Ternasky; Fuat Alican; Yigit Ihlamur (CoRR, 2025)

Policy Induction: Predicting Startup Success via Explainable Memory-Augmented In-Context Learning. - Xianling Mu; Joseph Ternasky; Fuat Alican; Yigit Ihlamur (CoRR, 2025)

Random Rule Forest (RRF): Interpretable Ensembles of LLM-Generated Questions for Predicting Startup Success. - Ben Griffin; Joseph Ternasky; Fuat Alican; Yigit Ihlamur (CoRR, 2025)