3 papers
cs.CL2025
eDIF: A European Deep Inference Fabric for Remote Interpretability of LLM
Irma Heithoff. Marc Guggenberger, Sandra Kalogiannis, Susanne Mayer +3
This paper presents a feasibility study on the deployment of a European Deep Inference Fabric (eDIF), an NDIF-compatible infrastructure designed to support mechanistic interpretabi…
cs.CL2025
Deception in LLMs: Self-Preservation and Autonomous Goals in Large Language Models
Sudarshan Kamath Barkur, Sigurd Schacht, Johannes Scholl
Recent advances in Large Language Models (LLMs) have incorporated planning and reasoning capabilities, enabling models to outline steps before execution and provide transparent rea…
cs.CL2024
Inference Optimizations for Large Language Models: Effects, Challenges, and Practical Considerations
Leo Donisch, Sigurd Schacht, Carsten Lanquillon
Large language models are ubiquitous in natural language processing because they can adapt to new tasks without retraining. However, their sheer scale and complexity present unique…