Yigit Ihlamur

According to our database, Yigit Ihlamur authored at least 8 papers between 2023 and 2025.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of five.

2025

Random Rule Forest (RRF): Interpretable Ensembles of LLM-Generated Questions for Predicting Startup Success.

Ben Griffin, Joseph Ternasky, Fuat Alican, Yigit Ihlamur

CoRR, May, 2025

Policy Induction: Predicting Startup Success via Explainable Memory-Augmented In-Context Learning.

Xianling Mu, Joseph Ternasky, Fuat Alican, Yigit Ihlamur

CoRR, May, 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, April, 2025

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, January, 2025

2024

GPTree: Towards Explainable Decision-Making via LLM-powered Decision Trees.

Sichao Xiong, Yigit Ihlamur, Fuat Alican, Aaron Ontoyin Yin

CoRR, 2024

Automating Venture Capital: Founder assessment using LLM-powered segmentation, feature engineering and automated labeling techniques.

Ekin Ozince, Yigit Ihlamur

CoRR, 2024

An Automated Startup Evaluation Pipeline: Startup Success Forecasting Framework (SSFF).

Xisen Wang, Yigit Ihlamur

CoRR, 2024

2023

Founder-GPT: Self-play to evaluate the Founder-Idea fit.

Sichao Xiong, Yigit Ihlamur

CoRR, 2023