@inproceedings{xie-etal-2025-awareness,
    title = "From Awareness to Adaptability: Enhancing Tool Utilization for Scientific Reasoning",
    author = "Xie, Wenjing  and
      Liang, Xiaobo  and
      Li, Juntao  and
      Wang, Wanfu  and
      Chen, Kehai  and
      Zhu, Qiaoming  and
      Zhang, Min",
    editor = "Che, Wanxiang  and
      Nabende, Joyce  and
      Shutova, Ekaterina  and
      Pilehvar, Mohammad Taher",
    booktitle = "Findings of the Association for Computational Linguistics: ACL 2025",
    month = jul,
    year = "2025",
    address = "Vienna, Austria",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingestion-acl-25/2025.findings-acl.461/",
    pages = "8811--8831",
    ISBN = "979-8-89176-256-5",
    abstract = "As large language models (LLMs) are increasingly applied to complex scientific problem-solving, their effectiveness is often limited by unconscious or failed tool usage. To address this issue, we introduce the Tool-Awareness Training (TAT) method, designed to enhance scientific reasoning. This approach leverages both forward and backward data generation strategies to strengthen the model{'}s conscious and selective tool utilization in multi-step reasoning tasks. Our method unfolds in three stages: (1) developing tool-knowledge through backward tooluse data generation (2) enhancing tool-awareness in multi-step reasoning by utilizing forward reasoning data, and (3) improving domain adaptability through large-scale domain-specific data for multi-task learning. These three stages progressively establish the foundation for tool learning and scientific reasoning, effectively integrating both, enabling the model to tackle multi-domain scientific tasks while optimizing tool usage. Our experimental results demonstrate that TAT significantly enhances LLM performance in mathematical and scientific reasoning tasks, particularly by improving the model{'}s tool utilization capabilities, including proactivity and execution success rates."
}