3 papers
cs.LG2026
Decomposing the Generalization Gap in PROTAC Activity Prediction: Variance Attribution and the Inter-Laboratory Ceiling
Thor Klamt, Wolfgang Nejdl, Ming Tang
Machine-learning predictors of biochemical activity often exhibit large random-split-to-leave-one-target-out generalisation gaps that have been documented but not decomposed. We fr…
cs.CL2026
LGSE: Lexically Grounded Subword Embedding Initialization for Low-Resource Language Adaptation
Hailay Teklehaymanot, Dren Fazlija, Wolfgang Nejdl
Adapting pretrained language models to low-resource, morphologically rich languages remains a significant challenge. Existing vocabulary expansion methods typically rely on arbitra…
cs.CV2026
Investigating the Impact of Histopathological Foundation Models on Regressive Prediction of Homologous Recombination Deficiency
Alexander Blezinger, Wolfgang Nejdl, Ming Tang
Foundation models pretrained on large-scale histopathology data have found great success in various fields of computational pathology, but their impact on regressive biomarker pred…