AI RESEARCH

Memory Transfer Learning: How Memories are Transferred Across Domains in Coding Agents

arXiv CS.AI

ArXi:2604.14004v1 Announce Type: new Memory-based self-evolution has emerged as a promising paradigm for coding agents. However, existing approaches typically restrict memory utilization to homogeneous task domains, failing to leverage the shared infrastructural foundations, such as runtime environments and programming languages, that exist across diverse real-world coding problems. To address this limitation, we investigate \textbf{Memory Transfer Learning} (MTL) by harnessing a unified memory pool from heterogeneous domains.