arXiv:2212. 05260v4 Announce Type: replace-cross Abstract: Proper scoring rules encourage probabilistic predictions that match the true underlying distribution and are central to model evaluation, with increasing relevance in automated workflows such as AutoML.
By John Zobolas, Raphael Sonabend, Riccardo De Bin, Johannes Piller, Philipp Kopper, Lukas Burk, Andreas Bender
arXiv:2506. 02075v3 Announce Type: replace-cross Abstract: The current state of evaluation in survival analysis is plagued by the persistent use of evaluation metrics in ways that are misaligned with the stated modeling objective.
By Christian Marius Lillelund, Shi-ang Qi, Russell Greiner, Christian Fischer Pedersen
arXiv:2608. 08202v1 Announce Type: new Abstract: Data-centric curation pipelines frequently rely on model confidence scores to flag and filter noisy or mislabeled training instances.
By Sai Srikar Boddupalli
arXiv:2606. 18479v1 Announce Type: new Abstract: Reject inference methods are widely used to mitigate survival bias in credit scoring, yet their effectiveness remains poorly understood.
By Bruno Scarone, Ricardo Baeza-Yates
arXiv:2607. 10466v1 Announce Type: new Abstract: Survival models can model time-to-event outcomes using partially observed data.
By Yanqi Xu, Hui Dai, Carlos Fernandez-Granda, Krzysztof J. Geras, Yiqiu Shen
arXiv:2608. 02665v1 Announce Type: cross Abstract: A benchmark score is a measurement instrument, yet most benchmarks read each item at a single canonical surface form.
By Yongxi Zhou, Junwei Yao, Yuanzhe Liu, Zihan Dong, Wenbo Ye, Jiaxi Wen, Lai Yun Choi