5 papers
TACTICL: Task-Aware Compression of Tabular ICL Models
Mykhailo Koshil, Matthias Feurer, Katharina Eggensperger
The strong performance of foundation models for tabular tasks comes at substantial inference costs. Distilling models into task-specific architectures reduces model size and comput…
Is One Layer Enough? Understanding Inference Dynamics in Tabular Foundation Models
Amir Rezaei Balef, Mykhailo Koshil, Katharina Eggensperger
Transformer-based tabular foundation models (TFMs) dominate small to medium tabular predictive benchmark tasks, yet their inference mechanisms remain largely unexplored. We present…
Towards Understanding Layer Contributions in Tabular In-Context Learning Models
Amir Rezaei Balef, Mykhailo Koshil, Katharina Eggensperger
Despite the architectural similarities between tabular in-context learning (ICL) models and large language models (LLMs), little is known about how individual layers contribute to…
AnomalousPatchCore: Exploring the Use of Anomalous Samples in Industrial Anomaly Detection
Mykhailo Koshil, Tilman Wegener, Detlef Mentrup +2
Visual inspection, or industrial anomaly detection, is one of the most common quality control types in manufacturing. The task is to identify the presence of an anomaly given an im…
Trixi the Librarian
Fabian Wieczorek, Shang-Ching Liu, Björn Sygo +1
In this work, we present a three-part system that automatically sorts books on a shelf using the PR- 2 platform. The paper describes a methodology to sufficiently detect and recogn…