@inproceedings{chen-etal-2026-beyond-code,
    title = "Beyond Code Pairs: Dialogue-Based Data Generation for {LLM} Code Translation",
    author = "Chen, Le  and
      Xu, Nuo  and
      Chen, Winson  and
      Lei, Bin  and
      Lin, Pei-Hung  and
      Zhou, Dunzhi  and
      Thakur, Rajeev  and
      Ding, Caiwen  and
      Jannesari, Ali  and
      Liao, Chunhua",
    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.1557/",
    pages = "33781--33803",
    ISBN = "979-8-89176-390-6",
    abstract = "Large language models (LLMs) have shown remarkable capabilities in code translation, yet their performance deteriorates in low-resource programming domains such as Fortran and emerging frameworks like CUDA, where high-quality parallel data are scarce. We present an automated dataset generation pipeline featuring a dual-LLM Questioner{--}Solver design that incorporates external knowledge from compilers and runtime feedback. Beyond traditional source{--}target code pair datasets, our approach additionally generates (1) verified translations with unit tests for assessing functional consistency, and (2) multi-turn dialogues that capture the reasoning process behind translation refinement. Applied to Fortran{\textrightarrow}C++ and C++{\textrightarrow}CUDA, the pipeline yields 3.64k and 3.93k dialogues, respectively. Fine-tuning on this data yields dramatic improvements in functional correctness, boosting unit test success rates by over 56{\%} on the challenging C++-to-CUDA task. We show that the generated data enables a 7B open-weight model to significantly outperform larger proprietary systems on key metrics like compilation success."
}