[Stanley]

Inside the Model That Outsmarts Popular AI Detection Tools

Most AI detectors only label entire documents as human or machine written. This paper introduces a model that identifies exactly which words were generated by AI inside mixed text. Tested across domains, generators, and boundary positions, it outperforms popular proprietary tools and generalizes well to unseen LLMs, including instruction-tuned models.


https://hackernoon.com/inside-the-model-...source=rss

[shakur123]

As generation models improve and blend stylistically with human writing, detection will always lag behind. The real challenge isn’t just accuracy — it’s robustness against adversarial editing and real-world mixed workflows.