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| title: mithridatium | |
| authors: | |
| - given-names: Pelumi | |
| family-names: Oluwategbe | |
| email: pelumi.oluwategbe@slu.edu | |
| affiliation: Saint Louis University | |
| - given-names: William | |
| family-names: Phoenix | |
| email: will.phoenix@slu.edu | |
| affiliation: Saint Louis University | |
| - given-names: Gustavo | |
| family-names: Lucca | |
| email: gustavo.lucca@slu.edu | |
| affiliation: Saint Louis University | |
| - given-names: Payton | |
| family-names: Guffey | |
| email: payton.guffey@slu.edu | |
| affiliation: Saint Louis University | |
| cff-version: 1.2.0 | |
| message: If you use this software, please cite it using the metadata from this file. | |
| type: software | |
| abstract: Mithridatium is a research-driven project aimed at detecting backdoors | |
| and data poisoning in downloaded pretrained models or pipelines (e.g., from | |
| Hugging Face). Our goal is to provide a modular, command-line tool that | |
| helps researchers and engineers trust the models they use. | |
| keywords: | |
| - data privacy | |
| - machine-learning | |
| - python | |
| - security | |
| license: MIT-Modern-Variant | |
| repository-code: https://github.com/oss-slu/mithridatium | |