@inproceedings{singh-etal-2026-grammar,
    title = "Grammar Search for Multi-Agent Systems",
    author = "Singh, Mayank  and
      Yadav, Vikas  and
      Malay, Shiva Krishna Reddy  and
      Nayak, Shravan  and
      Rajeswar, Sai  and
      Madhusudhan, Sathwik Tejaswi  and
      Blanco, Eduardo",
    editor = "Liakata, Maria  and
      Moreira, Viviane P.  and
      Zhang, Jiajun  and
      Jurgens, David",
    booktitle = "Proceedings of the 64th Annual Meeting of the {A}ssociation for {C}omputational {L}inguistics (Volume 1: Long Papers)",
    month = jul,
    year = "2026",
    address = "San Diego, California, United States",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest-acl/2026.acl-long.75/",
    pages = "1640--1655",
    ISBN = "979-8-89176-390-6",
    abstract = "Automatic search for Multi-Agent Systems has recently emerged as a key focus in agentic AI research. Several prior approaches have relied on LLM-based free-form search over the code space. In this work, we propose a more structured framework that explores the same space through a fixed set of composable components. We show that, despite lacking the generative flexibility of LLMs during the candidate generation stage, our method outperforms prior approaches on a majority of evaluated benchmarks across two backbone LLMs and two domains: mathematics and question answering. Furthermore, our method offers additional advantages, including a more cost-efficient search process and the generation of modular, interpretable multi-agent systems."
}