Papers by Ufaq Khan

1 papers
DAMASHA: Detecting AI in Mixed Adversarial Texts via Segmentation with Human-interpretable Attribution (2026.findings-eacl)

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Challenge: a new framework for mixed authorship detection addresses the challenge of segmenting mixed-authorship text . mixed-authored text detection is a growing concern in the age of advanced large language models . a recent survey highlighted the greater challenges of detecting AI content in realworld settings .
Approach: They propose a framework for mixed authorship detection that integrates stylometric cues, perplexity-driven signals, and structured boundary modeling to accurately segment collaborative human-AI content.
Outcome: The proposed framework improves robustness against adversarial perturbations while revealing limitations.

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