[AAAI 2025 oral] Official repository of Imitate Before Detect: Aligning Machine Stylistic Preference for Machine-Revised Text Detection

This project aims to address this gap by conducting a systematic, controlled study of human versus LLM-generated text detectability using paired question–answer datasets. Rather than proposing a novel detection architecture, the focus is on analyzing detection robustness, failure modes, and the impact of adversarial humanization strategies.

Detect and eliminate AI writing patterns in your content. This Claude Code plugin performs multi-tier analysis of character patterns, language cues, structural issues, and voice authenticity. Auto-fix em dashes, smart quotes, and emojis. Keep documentation and prose sounding genuinely human.

Professional text refinement, AI detection, and style conversion services. 专业文本润色、AI检测和风格转换服务

Python tool for simple comparison check on generated code vs suspected generated code.

Projects concerning LLMs, prompting, NLP, webscraping, data aquisition and dataset analysis.

🎲 Detect whether a GitHub repo's code was likely written by an LLM. Zero dependencies. Scores repos 0-100 using commit velocity, session analysis, burst detection, message patterns, and project-scale plausibility.

🔍 Code governance & AI validation tool - Catch oversimplified stubs, hallucinated APIs, and incomplete logic. 50+ checks, SARIF reports. Part of the NAAb Ecosystem.

6-class text authorship detection pipeline for human and LLM-generated text using TF-IDF, stylometric features, and stacked scikit-learn/LightGBM models for the MALTO Hackathon 2026 (F1: 0.9567).

Proof of concept tool to bypass document replay technology (such as GPTZero).

A unified tool for testing and using LLM detectors

MCP server for the Chief Editor AI slop detector — analyses text for AI-generated writing patterns

Detects AI-generated essays using an ensemble of LightGBM, CatBoost, Naive Bayes, SGD, and Random Forest. Custom BPE tokenizer built with Hugging Face + TF-IDF vectorization with 3-5 word n-grams. Weighted soft-voting classifier.

Engine for detecting LLM-generated credentials. (Beta)

Extension Chrome MV3 de détection de contenus générés par IA (texte, images, vidéos, audio). Heuristiques locales, APIs externes optionnelles, signalement communautaire et inspection HTML/sécurité.

Detect if a GitHub repo’s code was likely generated by an LLM using commit timing patterns without relying on dependencies or complex setup.