Year: 2025
Type: preprint
Abstract: 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.
Source: arXiv (Cornell University)
Authors: Alshomary, Milad, Bhatnagar, Anisha, Zeng, Peter, Muresan, Smaranda, Rambow, Owen, McKeown, Kathleen
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7111182172
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