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cs.CY2025
Narrowing the Gap: Supervised Fine-Tuning of Open-Source LLMs as a Viable Alternative to Proprietary Models for Pedagogical Tools
Lorenzo Lee Solano, Charles Koutcheme, Juho Leinonen +2
Frontier Large language models (LLMs) like ChatGPT and Gemini can decipher cryptic compiler errors for novice programmers, but their computational scale, cost, and tendency to over…
cs.CL2025★ 1 cited
Supervised Fine-Tuning LLMs to Behave as Pedagogical Agents in Programming Education
Emily Ross, Yuval Kansal, Jake Renzella +2
Large language models (LLMs) are increasingly being explored in higher education, yet their effectiveness as teaching agents remains underexamined. In this paper, we present the de…