2 papers
cs.LG2026
Probabilistic Label Spreading: Efficient and Consistent Estimation of Soft Labels with Epistemic Uncertainty on Graphs
Jonathan Klees, Tobias Riedlinger, Peter Stehr +3
Safe artificial intelligence for perception tasks remains a major challenge, partly due to the lack of data with high-quality labels. Annotations themselves are subject to aleatori…
cs.CV2026
From Label Error Detection to Correction: A Modular Framework and Benchmark for Object Detection Datasets
Sarina Penquitt, Jonathan Klees, Rinor Cakaj +3
Object detection has advanced rapidly in recent years, driven by increasingly large and diverse datasets. However, label errors often compromise the quality of these datasets and a…