Update | AI Detection & AI Image Detection

[Danny991111]

Lynote AI v2.0 Official Release

We’re glad to launch the new version of our open-source academic toolkit for all student users.

✨ New Features Added

1. AI Text Detector: Built-in full-text AI content scanning tool. It accurately distinguishes human original writing and AI-generated paragraphs, generates detailed originality score reports, and highlights all high-risk AI-written fragments to help students avoid academic audit penalties. https://github.com/lynote-ai/ai-text-detector
2. AI Image Detection: Brand-new visual authenticity inspection tool, precisely identify AI-generated fake illustrations, thesis figures and chart images. The function automatically marks distorted textures, unnatural facial/hand structures and other typical AI drawing flaws, outputting a complete authenticity analysis report for academic submission compliance.https://github.com/lynote-ai/ai-image-detector

🛠️ Optimizations & Bug Fixes

• Optimized AI humanizer rewriting speed for long essays
• Fixed flashcard text formatting error when importing PDF
• Improved audio transcription accuracy for multi-speaker lectures

🔗 Useful Links

⭐ Star this repo to support our continuous open-source iteration
🌐 Unlock unlimited full AI Text Detector & AI Image Detection advanced capabilities: https://lynote.ai
💬 If you meet any bugs or usage troubles, start a thread in Q&A section.

[rishabhsaini282]

Thanks for opening this discussion! One thing I've found while experimenting with AI-generated content is that evaluating why text appears AI-generated is often more useful than simply trying to rewrite it. Sentence-level analysis and confidence scoring can reveal recurring writing patterns and help improve the content while preserving its meaning.

I recently explored Pangram AI, which provides document uploads, sentence-level highlighting, and section-wise confidence analysis, and recorded a walkthrough of the workflow here: https://youtu.be/5h3qE_9pAzU?si=tV8KDBGutxUC020u.

I'm curious, has anyone compared humanized text against multiple AI detection tools to see how consistently different detectors evaluate the same document, rather than relying on just one detector?

[Danny991111]

Hi, someone has indeed conducted such a comparison. You can check out this article, which compares various AI humanizer tools to see if they can pass evaluations by mainstream AI detectors: https://lynote.ai/blog/best-ai-humanizer-tools