54 citations · 126 across the 51 of their papers we have counts for
6 papers · 2 filters
Evaluating and Benchmarking the System One Model Jev
Tobias Deußer, Lorenz Sparrenberg, Rafet Sifa
Jev is a commercial System One model from TypeSafe AI that does not generate text: given a state and typed questions, it returns a choice from fixed options, a position on a rubric…
Automated Regulatory Compliance Question Answering in Financial Services with Domain-Adapted Retrieval-Augmented Generation
Tobias Deußer, Abhishek Pillai, Aurelio F. Bariviera +5
Financial institutions operate under dense, frequently amended rulebooks, and answering a compliance question correctly requires not only fluency but verifiable grounding in the au…
On the Impact of Anonymization on the Performance of Large Language Models
Tobias Deußer, Max Hahnbück, Lorenz Sparrenberg +3
As large language models are increasingly deployed in sensitive domains, anonymizing input data to protect personally identifiable information has become a critical practice. Howev…
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…
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…
Domain-Adaptation through Synthetic Data: Fine-Tuning Large Language Models for German Law
Ali Hamza Bashir, Muhammad Rehan Khalid, Kostadin Cvejoski +7
Large language models (LLMs) often struggle in specialized domains such as legal reasoning due to limited expert knowledge, resulting in factually incorrect outputs or hallucinatio…