Joseph Ternasky

According to our database, Joseph Ternasky authored at least 7 papers between 2025 and 2026.

Collaborative distances:

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

2026

CoFEE: Reasoning Control for LLM-Based Feature Discovery.

Maximilian Westermann, Ben Griffin, Aaron Ontoyin Yin, Zakari Salifu, Yagiz Ihlamur, Kelvin Amoaba, Joseph Ternasky, Fuat Alican, Yigit Ihlamur

CoRR, April, 2026

From Stochastic Answers to Verifiable Reasoning: Interpretable Decision-Making with LLM-Generated Code.

Anirudh Jaidev Mahesh, Ben Griffin, Fuat Alican, Joseph Ternasky, Zakari Salifu, Kelvin Amoaba, Yagiz Ihlamur, Aaron Ontoyin Yin, Aikins Laryea, Afriyie Kwesi Samuel, Yigit Ihlamur

CoRR, March, 2026

2025

LLM-AR: LLM-powered Automated Reasoning Framework.

Rick Chen, Joseph Ternasky, Aaron Ontoyin Yin, Xianling Mu, Fuat Alican, Yigit Ihlamur

CoRR, October, 2025

VCBench: Benchmarking LLMs in Venture Capital.

Rick Chen, Joseph Ternasky, Afriyie Samuel Kwesi, Ben Griffin, Aaron Ontoyin Yin, Zakari Salifu, Kelvin Amoaba, Xianling Mu, Fuat Alican, Yigit Ihlamur

CoRR, September, 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