collaborators

22 papers

cs.CV2026

Leveraging Transfer Learning with Class-Specific Decoders for Laparoscopic Segmentation

Priya Tomar, Aditya Parikh, Christian Bauckhage +1

Effective multi-organ segmentation in surgical data requires learning the intricate anatomical features and alleviating the challenge of class imbalance, which results from relativ…

cs.CV2026

First Investigation of Deep Learning for Intraoperative Gauze Segmentation in Minimally Invasive Abdominal Surgery

Priya Tomar, Maximilian Broß, Philipp Feodorovici +7

Surgical gauze is an essential part of surgical procedures, primarily used for controlling bleeding and absorbing bodily fluids. The post-surgical retention of gauze can lead to se…

cs.CV2026

Hybrid Deep Learning for Traceability and Classification of Industrial Slate Tiles

Soren Antebi, Stefan Eickeler, Sandra Halscheidt +4

Applying deep learning to instance-aware reidentification of slate tiles and extraction site classification can improve production efficiency and quality control in the slate tile…

cs.CV2026

Knowing When Not to Predict: Self Supervised Learning and Abstention for Safer DR Screening

Muskaan Chopra, Lorenz Sparrenberg, Jan H. Terheyden +1

Self-supervised learning (SSL) is now a standard way to pretrain medical image models, but performance is still mostly judged by downstream accuracy. For safety-critical screening…

cs.CL2026

Is continuous CoT better suited for multi-lingual reasoning?

Ali Hamza Bashir, Behzad Shomali, Markus Frey +3

We investigate whether performing reasoning in a continuous latent space leads to more robust multilingual capabilities. We compare Continuous Chain-of-Thought (using the CODI fram…

cs.CL2026

Towards Reliable Machine Translation: Scaling LLMs for Critical Error Detection and Safety

Muskaan Chopra, Lorenz Sparrenberg, Rafet Sifa

Machine Translation (MT) plays a pivotal role in cross-lingual information access, public policy communication, and equitable knowledge dissemination. However, critical meaning err…