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Detecting GPT-Assisted Writing Using Interpretable Stylometric Features

Paper recorded by Signals 4 on 2026-09-22 in cs.CL. Abstract reproduced from arXiv; link to the original below.

Published 2026-09-22 on arXiv · recorded by Signals 4 on 2026-09-23

Category: cs.CL · 自然语言处理 · first seen 2026-09-23

Abstract

Distinguishing GPT-assisted from independently authored student writing has become a critical challenge in academia. This paper evaluates the discriminative capability of interpretable stylometric features extracted solely from submitted text. Using data from 90 participants who wrote both independently and with ChatGPT assistance, we evaluate eight machine learning classifiers while keeping data

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#3 most recent of 227 cs.CL papers we have recorded · ↑ newer: Agensh: Scaling Organizational Intelligence to 1,024 Agents · ↓ older: Diffusion Drafts, AR Verifies: Accelerating Document OCR with Self-Spe
Cite this page: Detecting GPT-Assisted Writing Using Interpretable Stylometric Features: the #3 most recent of 227 cs.CL papers we have recorded (as of 2026-09-22). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/detecting-gpt-assisted-writing-using-interpretable-stylometric-features.html
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