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From the 1 of 10 linked papers with an AI index.

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10 papers

cs.LG2026

Directional Curvature from Armijo Backtracking: A Low-Cost Sharpness Probe and a Calibration-Free Learning-Rate Safeguard for Adam

Ashmitha R, Jörg Frochte, Jörg Frochte

The paper shows that the step size accepted by a single Armijo backtracking line search can be used as a cheap estimator of directional curvature (sharpness) and leverages this to…

cs.LG2026

Physics-Informed Machine Learning Under Small-Data Constraints: Lessons from Abrasive Waterjet Milling

Sarah Grewe, Jörg Frochte

In physically dominated machining processes, experimental datasets are small, expensive, and material-specific; in this regime, data curation, evaluation design, and the form of ph…

cs.LG2026

Multi-Class vs. Multi-Label BERT for CVE-to-CWE Mapping: How Taxonomy Structure Shapes the Errors

Ana Schwengber Kelm, Christian Bockermann, Jörg Frochte

Assigning Common Weakness Enumeration (CWE) categories to Common Vulnerabilities and Exposures (CVE) records remains an important but largely manual step in vulnerability analysis.…

cs.CV2026

When Style Similarity Scores Fail: Diagnosing Raw CSD Cosine in Artist-Style Evaluation

Jörg Frochte

Raw cosine in the 768-dimensional output space of the Contrastive Style Descriptor (CSD) is now widely read as an absolute, calibrated style-fidelity score for text-to-image and st…

cs.LG2026

Multiple Additive Neural Networks for Structured and Unstructured Data

Janis Mohr, Jörg Frochte

This paper extends and explains the Multiple Additive Neural Networks (MANN) methodology, an enhancement to the traditional Gradient Boosting framework, utilizing nearly shallow ne…

cs.AI2026

LLMs for Text-Based Exploration and Navigation Under Partial Observability

Stephan Sandfuchs, Maximilian Melchert, Jörg Frochte

Exploration and goal-directed navigation in unknown layouts are central to inspection, logistics, and search-and-rescue. We ask whether large language models (LLMs) can function as…