XAM: Interactive Explainability for Authorship Attribution Models
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arXiv
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| Main Authors: | , , , , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866917131905400832 |
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| author | Alshomary, Milad Bhatnagar, Anisha Zeng, Peter Muresan, Smaranda Rambow, Owen McKeown, Kathleen |
| author_facet | Alshomary, Milad Bhatnagar, Anisha Zeng, Peter Muresan, Smaranda Rambow, Owen McKeown, Kathleen |
| contents | We present IXAM, an Interactive eXplainability framework for Authorship Attribution Models. Given an authorship attribution (AA) task and an embedding-based AA model, our tool enables users to interactively explore the model's embedding space and construct an explanation of the model's prediction as a set of writing style features at different levels of granularity. Through a user evaluation, we demonstrate the value of our framework compared to predefined stylistic explanations. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2512_06924 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | XAM: Interactive Explainability for Authorship Attribution Models Alshomary, Milad Bhatnagar, Anisha Zeng, Peter Muresan, Smaranda Rambow, Owen McKeown, Kathleen Computation and Language We present IXAM, an Interactive eXplainability framework for Authorship Attribution Models. Given an authorship attribution (AA) task and an embedding-based AA model, our tool enables users to interactively explore the model's embedding space and construct an explanation of the model's prediction as a set of writing style features at different levels of granularity. Through a user evaluation, we demonstrate the value of our framework compared to predefined stylistic explanations. |
| title | XAM: Interactive Explainability for Authorship Attribution Models |
| topic | Computation and Language |
| url | https://arxiv.org/abs/2512.06924 |