{"ID":5439484,"CreatedAt":"2026-07-01T01:17:58.482524686Z","UpdatedAt":"2026-07-02T19:06:01.127452785Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2606.30846","arxiv_id":"2606.30846","title":"How Can AI Find My Model? A Model-Finding Experimental Study Considering Data Formats, Embeddings, and Retrieval Strategies","abstract":"Discovering simulation models for reuse remains a fundamental challenge in Modeling and Simulation (M\u0026S). When many models coexist, identifying those that align with a given modeling intent remains difficult. Recent advances in Artificial Intelligence (AI), particularly retrieval-based approaches, offer a promising pathway to operate at this semantic layer. In this paper, we present an experimental study investigating the impact of data representation, transformer-based embedding models, and retrieval strategies on the discovery of simulation models using natural language queries. We evaluated performance across multiple query types using standard information retrieval metrics, including recall@5 and nDCG@5. Results show that data representation matters, open-source embedding models can achieve high performance, and reranking methods are important, especially as query complexity increases. This work provides a baseline for AI-driven model discovery and discusses its role in advancing toward AI-driven composability and interoperability.","short_abstract":"Discovering simulation models for reuse remains a fundamental challenge in Modeling and Simulation (M\u0026S). When many models coexist, identifying those that align with a given modeling intent remains difficult. Recent advances in Artificial Intelligence (AI), particularly retrieval-based approaches, offer a promising pat...","url_abs":"https://arxiv.org/abs/2606.30846","url_pdf":"https://arxiv.org/pdf/2606.30846v1","authors":"[\"Jhon G. Botello\",\"Jose J. Padilla\",\"Erika Frydenlund\",\"Krzysztof Rechowicz\",\"Eric Weisel\"]","published":"2026-06-29T19:23:32Z","proceeding":"cs.AI","tasks":"[\"cs.AI\"]","methods":"[\"Transformer\"]","has_code":false}