output
20022026
most citedA Comprehensive Survey on Model Quantization for Deep Neural Networks in Image Classification

224 citations

44 papers

eess.SY2026

Optical Detuning Strategies for Shielded Loop Resonators

Jakob Gerlach, Reza Aghabagheri, Zining Liu +5

Purpose: To compare detuning performance and evaluate the power requirements of optical detuning methods, and to demonstrate the feasibility of an optically detuned four-channel re…

cs.LG2026

SurvPFN: Towards Foundation Models for Survival Predictions

Samuel Böhm, Lennart Purucker, Frank Hutter +1

Tabular foundation models (TFMs) have made rapid progress in standard classification and regression, but time-to-event survival prediction tasks have remained largely untouched. Un…

cs.CV2026

Scalable Training of Spatially Grounded 2D Vision-Language Models for Radiology

Yusuf Salcan, Simon Ging, Robin Tibor Schirrmeister +4

We study how to train visually grounded vision-language models (VLMs) for radiology without manual spatial annotations. We introduce RefRad2D, a large-scale bilingual (German/Engli…

cs.CL2026

The Word and the Way: Strategies for Domain-Specific BERT Pre-Training in German Medical NLP

Henry He, Johann Frei, Raphael Schmitt

Digital healthcare generates vast amounts of clinical text that can support AI-assisted applications, yet German biomedical language models remain limited by older architectures or…

stat.ME2026

Learning study similarity to investigate heterogeneity in meta-analysis using LLMs and triplet loss

Kanella Panagiotopoulou, Harald Binder, Theodoros Evrenoglou

Meta-analyses of observational studies often show substantial between-study heterogeneity, limiting the interpretability of pooled estimates. Meta-regression can be used to explore…

cs.CV2026

Learning to Read Where to Look: Disease-Aware Vision-Language Pretraining for 3D CT

Simon Ging, Philipp Arnold, Sebastian Walter +6

Recent 3D CT vision-language models align volumes with reports via contrastive pretraining, but typically rely on limited public data and provide only coarse global supervision. We…