arxivcs.LGcs.CL2026-07-16
Leveraging Instruction Tuning and Merging for Reasoning Model Adaptation
Yu-Du Feng, Niels Mündler-Sasahara, Mark Vero, Martin Vechev
Reasoning language models (RLMs) have demonstrated impressive performance in domains such as mathematics and coding. These domains permit reliable verification of model outputs, which is important for enabling the reinforcement learning that drives RLM performance gains. However,…