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Hey, really impressive results, it's actually passing GPTZero on dense technical text, which I haven't seen from any other humanizer tool. Would you be willing to share the underlying model/pipeline, or at least explain the approach you used (e.g. is it a local model, an LLM API with a specific prompt, a translation-chain technique, or something else)? I'm trying to understand and reproduce something similar for my own use case, and a rough explanation of the mechanism would be hugely helpful. Thanks either way!