Imalwayshere/Open-Detector
BERT-based AI-generated academic text detection model
Built on BERT-base-uncased with binary classification, the model achieves 99.57% accuracy on ~1.4M academic text samples while maintaining a 0.82% false positive rate and 99.94% recall. Weights are distributed via Hugging Face and integrate directly with the `transformers` library, supporting inference through standard PyTorch workflows with 512-token context windows. Beyond stylometric detection, the project roadmap includes fact-checking, citation verification, and hallucination detection to focus on content authenticity rather than writing style alone.
220 stars.
Stars
220
Forks
43
Language
Python
License
MIT
Category
Last pushed
Nov 01, 2025
Commits (30d)
0
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