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The first comprehensive empirical study of MTL for PPM is presented, evaluating a variety of task combinations, neural architectures, and optimization methods and finding substantial improvements in next-activity prediction and inherent mitigation of class imbalance using MTL.
Large language models typically undergo post-training to align them with safety policies but there exist many sophisticated jailbreaks that sidestep established safeguards. For instance, prior work by Andriushchenko et al. (2025) has found that changing the grammatical tense from present to past can be enough to elicit...
This work argues that benchmark evaluation should also consider the data-centric peak performance frontier, defined by the best statistically supported performance achieved on each dataset, and finds that common aggregation metrics are highly correlated and largely measure consistency and avoiding failures, while being...
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