4 papers
Hybrid AI Patterns: Thirteen Ways to Couple Language Models with Rules, and How to Choose Among Them
Siegfried Handschuh, Götz-Henrik Wiegand, Lorena Raichle
Language models handle text well, and rule engines give conclusions with proofs. Systems that combine the two are usually described by example, and the same coupling turns up under…
Is More Data Worth the Cost? Dataset Scaling Laws in a Tiny Attention-Only Decoder
Götz-Henrik Wiegand, Lorena Raichle, Rico Städeli +3
Training Transformer language models is expensive, as performance typically improves with increasing dataset size and computational budget. Although scaling laws describe this tren…
Leveraging Generative AI for Enhancing Domain-Driven Software Design
Götz-Henrik Wiegand, Filip Stepniak, Patrick Baier
Domain-Driven Design (DDD) is a key framework for developing customer-oriented software, focusing on the precise modeling of an application's domain. Traditionally, metamodels that…
A Convexity-dependent Two-Phase Training Algorithm for Deep Neural Networks
Tomas Hrycej, Bernhard Bermeitinger, Massimo Pavone +2
The key task of machine learning is to minimize the loss function that measures the model fit to the training data. The numerical methods to do this efficiently depend on the prope…