We have 3 of 28 papers
We haven’t gathered this author’s papers yet. Follow them and we’ll fetch their work.
Not the right person? Other researchers publish under this name.
Evaluating model uncertainty on real-world data is challenging because each instance provides only a single observed label, leaving true conditional class probabilities unknown. To address this, we introduce ProbabilityBench, a benchmark that provides exact, instance-level class probabilities across three simulated tex...
DenMark is proposed, a semantic watermarking framework that injects key-dependent signals directly into the DLM denoising process and achieves the best results across all reported detection metrics in all 48 backbone-dataset-attack combinations.
The FeeBee framework is extended, originally proposed for evaluating Bayes-error estimators, to the optimal BER and AUC, and the resulting procedure provides practical evaluation scores without requiring knowledge of the optimum.
We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.
