What Makes AI Research Replicable? Executable Knowledge Graphs as Scientific Knowledge Representations

ArXi:2510.17795v3 Announce Type: replace-cross Replicating AI research is a crucial yet challenging task for large language model (LLM) agents. Existing approaches often struggle to generate executable code, primarily due to insufficient background knowledge and the limitations of retrieval-augmented generation (RAG) methods, which fail to capture latent technical details hidden in referenced papers. Furthermore, previous approaches tend to overlook valuable implementation-level code signals and lack structured knowledge representations that multi-granular retrieval and reuse.