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This work proposes a self-contained two-stage training method, requiring no distillation from a stronger model, no manual annotation, and no pre-existing ICW IF ability, and introduces $\mathsf{ICWBench}$, a benchmark of three verifiable ICW instruction families, each scored on both detectability and answer quality.
This work introduces a novel approach, \textit{CanaryTrace}, to safeguard the ownership of text datasets and effectively detect unauthorized use by RA-LLMs, and demonstrates high query efficiency, detectability, and consistency, along with minimal perturbation to the original dataset, all without compromising the perfo...
Across several benchmarks, it is shown that a plain, fully fine-tuned RoBERTa matches or exceeds the specialized detectors those benchmarks are built around, suggesting that progress in AI-generated text detection should be measured not only by in-distribution performance, but also by robustness under distribution shif...
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