CHiPS: Character Histograms and Positional Signals for Lightweight Authorship Attribution in Romanian Texts
We propose CHiPS, a lightweight character-level authorship attribution method for Romanian texts. All reported experiments are closed-set: the true author is one of the candidate authors in the training data. CHiPS studies two complementary fingerprints of writing style: CH-SVM, a character-histogram classifier based on one-character marginal distributions, and FFT12-LR, a positional-signal classifier that represents selected characters and punctuation classes as impulse trains (binary indicator sequences over character positions) and extracts Fourier/Welch spectral descriptors. We also report CHiPS-F, a leakage-safe decision-level fusion variant, and an optional top-5 listwise reranker t...
| Authors | Sanda-Maria Avram, George C. Ţurcaş |
|---|---|
| Primary category | cs.CL |
| Published | 24 July 2026 |
| Last updated at source | 24 July 2026 |
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