@inproceedings{yang-etal-2026-stcor,
    title = "{STCOR}: A Trilevel Syllogism-Driven Reasoning Framework",
    author = "Yang, Keying  and
      Wang, Hao  and
      Jian, Chengtao  and
      Yang, Kai",
    editor = "Elaraby, Mohamed  and
      Hautli-Janisz, Annette  and
      Romberg, Julia  and
      Musi, Elena  and
      Ruggeri, Federico  and
      Lawrence, John",
    booktitle = "Proceedings of the 13th Workshop on Argument Mining and Reasoning",
    month = jul,
    year = "2026",
    address = "San Diego, California, USA",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest-acl-workshops/2026.argmining-1.1/",
    pages = "1--4",
    ISBN = "979-8-89176-399-9",
    abstract = "Inspired by the human expert thinking paradigm in operations research, this work introduces a new concept of reasoning tasks: Textual Constrained Optimization (TCO) problems. A TCO problem is characterized by a natural language description that implicitly specifies an underlying structured model with variables, constraints, and objectives. We propose a novel Syllogism-driven Textual Constrained Optimization Reasoning (STCOR) paradigm, driven by classical syllogistic logic. Unlike contemporary stepwise methods, our framework structures reasoning into three phases: meta-modeling, which acts as the major premise by retrieving a relevant class-driven prototype template; formalization, which serves as the minor premise by instantiating the template into an explicit logical model from textual queries; and solving, which derives the final answer as conclusion. To support the end-to-end implementation, we further develop a tri-level optimization algorithm TriRL."
}