# AIDetection: A Generative AI Detection Tool for Educators Using Syntactic Matching of Common ASCII Characters As Potential 'AI Traces' Within Users' Internet Browser

arXiv: https://arxiv.org/abs/2503.16503 · HTML: https://mlsanity.com/paper/2503.16503/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 3 of its 17 references that are in the map.
- First posted on arXiv 12 Mar 2025.

## Builds on (most cited first, 3 of 3)

- [Delving into LLM-assisted writing in biomedical publications through excess vocabulary](https://mlsanity.com/paper/2406.07016/) (2024)
- [Will ChatGPT get you caught? Rethinking of Plagiarism Detection](https://mlsanity.com/paper/2302.04335/) (2023)
- [Perception, performance, and detectability of conversational artificial intelligence across 32 university courses](https://mlsanity.com/paper/2305.13934/) (2023)

## Abstract (arXiv)

This paper introduces a simple JavaScript-based web application designed to assist educators in detecting AI-generated content in student essays and written assignments. Unlike existing AI detection tools that rely on obfuscated machine learning models, AIDetection.info employs a heuristic-based approach to identify common syntactic traces left by generative AI models, such as ChatGPT, Claude, Grok, DeepSeek, Gemini, Llama/Meta, Microsoft Copilot, Grammarly AI, and other text-generating models and wrapper applications. The tool scans documents in bulk for potential AI artifacts, as well as AI citations and acknowledgments, and provides a visual summary with downloadable Excel and CSV reports. This article details its methodology, functionalities, limitations, and applications within educational settings.