AI RESEARCH
Self-Execution Simulation Improves Coding Models
arXiv CS.LG
•
ArXi:2604.03253v1 Announce Type: cross A promising research direction in enabling LLMs to generate consistently correct code involves addressing their inability to properly estimate program execution, particularly for code they generate. In this work, we nstrate that Code LLMs can be trained to simulate program execution in a step-by-step manner and that this capability can be leveraged to improve competitive programming performance.