@inproceedings{lyn-graham-2025-translatex,
    title = "{T}rans{L}a{T}e{X}: Exposing the Last-Mile Execution Gap in {LLM}-Agent for Scientific Formatting",
    author = "Lyn, Jiawen  and
      Graham, Yvette",
    editor = "Zhao, Wei  and
      D{'}Souza, Jennifer  and
      Eger, Steffen  and
      Lauscher, Anne  and
      Hou, Yufang  and
      Sadat Moosavi, Nafise  and
      Miller, Tristan  and
      Lin, Chenghua",
    booktitle = "Proceedings of The First Workshop on Human{--}LLM Collaboration for Ethical and Responsible Science Production (SciProdLLM)",
    month = dec,
    year = "2025",
    address = "Mumbai, India (Hybrid)",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest-ijcnlp-aacl/2025.sciprodllm-1.3/",
    pages = "19--24",
    ISBN = "979-8-89176-307-4",
    abstract = "Large Language Models (LLMs) have achieved remarkable progress in tasks such as survey writing and language polishing, yet the final stage of LaTeX formatting and template adaptation remains a neglected and error-prone bottleneck.We identify an execution illusion, where LLMs produce linguistically fluent but unexecutable LaTeX code.To address this, we introduce TransLaTeX{---}the first reasoning-and-control framework that converts documents between scholarly templates with compiler-level verifiability.TransLaTeX achieves three key innovations:(1) Structure{--}content separation via placeholder masking, ensuring privacy and less token consumption;(2) SafeFormatBench, the first benchmark dedicated to executable LaTeX generation and template conversion; and(3) Execution-grounded verification across compilation, policy compliance, and visual consistency.TransLaTeX outperforms Pandoc and full-text LLM baselines on SafeFormatBench in compilation rate, ACL policy compliance, and layout fidelity, effectively mitigating the execution illusion."
}