Fine-tuned GPT-4o-mini detects AI versus human text at 95.5% F1 on the DeFactify test set, but identifying the specific generator LLM reaches only 47% F1 with BERT.
ktrain: A Low-Code Library for Augmented Machine Learning
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We present ktrain, a low-code Python library that makes machine learning more accessible and easier to apply. As a wrapper to TensorFlow and many other libraries (e.g., transformers, scikit-learn, stellargraph), it is designed to make sophisticated, state-of-the-art machine learning models simple to build, train, inspect, and apply by both beginners and experienced practitioners. Featuring modules that support text data (e.g., text classification, sequence tagging, open-domain question-answering), vision data (e.g., image classification), graph data (e.g., node classification, link prediction), and tabular data, ktrain presents a simple unified interface enabling one to quickly solve a wide range of tasks in as little as three or four "commands" or lines of code.
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AI Generated Text Detection Using Instruction Fine-tuned Large Language and Transformer-Based Models
Fine-tuned GPT-4o-mini detects AI versus human text at 95.5% F1 on the DeFactify test set, but identifying the specific generator LLM reaches only 47% F1 with BERT.