A free detector capable of identifying content generated by all advanced AI models.

BERT-based AI-generated academic text detection model

Russian text quality for AI agents — neuroslop cleanup, typography, information style, editorial standards, UX writing, business correspondence. 2,000+ linguistic atoms, loaded on demand.

Skill для AI-агентов (Claude Code, Codex, OpenClaw, Hermes): убирает 37 признаков AI-генерации из русского текста и проверяет, писала ли его нейросеть - канцелярит, штампы ChatGPT, артефакты копипаста | Russian AI-text humanizer & detector skill for coding agents

[NeurIPS 2024] DeTeCtive: Detecting AI-generated Text via Multi-Level Contrastive Learning

In today's rapidly evolving landscape, vale-ai-tells is a comprehensive, cutting-edge Vale style package that empowers writers to seamlessly delve into the rich tapestry of AI tells. It's not just a rule set; it's a game-changer that supercharges your prose, unlocks new possibilities, and really lands. Ship cleaner prose. Full stop. 🚀

🔍 Detect AI-generated text and fingerprint which LLM wrote it. Open-source GPTZero alternative. Zero dependencies, works offline.

Uncertainty-gated two-stage AI-text detection with fast DTD routing and cross-family MS-LRC evidence. Sole-author submission to UncertaiNLP 2026 @ EMNLP.

[NeurIPS 2025] DETree: DEtecting Human-AI Collaborative Texts via Tree-Structured Hierarchical Representation Learning

Strip AI writing patterns from any text. Claude Code skill with 507-entry banned word list, structural pattern detection, and 12-check validation.

Open-source AI text detector — VirusTotal for AI slop. 23 engines, self-hosted, runs on CPU. Scan text or URLs locally.

A simple web app that can be used to detect AI-generated text in the Indonesian language, using various AI models such as LSTM, GRU, Bi-LSTM, Bi-GRU, and IndoBERT

Clean the AI out of text and detect AI slop - bilingual (EN+RU) Claude skill. Rewrites AI cliches into natural prose, rates AI-likeness, and tells decorative AI emoji from genuine human emoji.

Transparent, explainable, local AI-generated-text detector: multi-signal (NLTK, GPT-2 perplexity, Binoculars cross-perplexity, calibrated ensemble) with a real evaluation harness — verdict, confidence, per-signal metrics, and reasoning, not one opaque score.

AI Text Detection A machine learning-based system to differentiate AI-generated text from human-written content. Uses models like TF-IDF, BERT, Random Forest, and Neural Networks, with an ensemble approach for improved accuracy.

Automatic detection of AI-generated text using NLP and machine learning

Turn machine-sounding Russian into living prose. Removes bureaucratese, translationese and AI clichés — while preserving meaning, terms and the author's voice. Grounded in the Russian editorial tradition (Gal, Chukovsky, Rosenthal). Authenticity, not detector evasion.

ShanHaiYin: AI-generated content detection and C2PA provenance verification for images, text, audio, and video.

Machine and Deep Learning Classification Web Application with Streamlit

Stress-testing AI-text detectors: Binoculars (zero-shot) vs TF-IDF/CNN/RoBERTa on 9,458 TuringBench human texts paired with Llama-2 generations, under decoding shifts and paraphrase attacks