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Multi-scale Feature Fusion-based Dynamic Framework using Continual Learning to Identify Text Generated by Multiple Large Language Models
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DOI：10.1016/j.knosys.2025.115206.png)
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Abstract
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• Proposes a dynamic multi-scale feature fusion system for AI-text detection • Uses Elastic Weight Consolidation to retain prior knowledge during re-training • Achieves strong detection across diverse models and linguistic contexts • Detects AI-generated text from ChatGPT, GLM, FLAN-T5, LLaMA, and others • Easily retrainable to adapt to future AI text generation models
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