@inproceedings{khan-etal-2025-tokensmith,
    title = "{T}oken{S}mith: Streamlining Data Editing, Search, and Inspection for Large-Scale Language Model Training and Interpretability",
    author = "Khan, Mohammad Aflah  and
      Godbole, Ameya  and
      Wei, Johnny  and
      Wang, Ryan Yixiang  and
      Flemings, James  and
      Gummadi, Krishna P.  and
      Neiswanger, Willie  and
      Jia, Robin",
    editor = {Habernal, Ivan  and
      Schulam, Peter  and
      Tiedemann, J{\"o}rg},
    booktitle = "Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing: System Demonstrations",
    month = nov,
    year = "2025",
    address = "Suzhou, China",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest-emnlp/2025.emnlp-demos.50/",
    pages = "678--687",
    ISBN = "979-8-89176-334-0",
    abstract = "Understanding the relationship between training data and model behavior during pretraining is crucial, but existing workflows make this process cumbersome, fragmented, and often inaccessible to researchers. We present TokenSmith, an open-source library for interactive editing, inspection, and analysis of datasets used in Megatron-style pretraining frameworks such as GPT-NeoX, Megatron, and NVIDIA NeMo. TokenSmith supports a wide range of operations including searching, viewing, exporting, inspecting, and sampling data, all accessible through a simple user interface and a modular backend. It also enables structured editing of pretraining data without requiring changes to training code, simplifying dataset debugging, validation, and experimentation. TokenSmith is designed as a plug-and-play addition to existing large language model pretraining workflows, thereby democratizing access to production-grade dataset tooling. TokenSmith is hosted on GitHub (https://github.com/aflah02/TokenSmith), with accompanying documentation and tutorials (https://aflah02.github.io/TokenSmith/). A demonstration video is also available on YouTube (https://www.youtube.com/watch?v=cDO8VE9fZvU)"
}