19 citations · 19 across the 5 of their papers we have counts for
5 papers
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…
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…
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…
PHOENIX: Open-Source Language Adaption for Direct Preference Optimization
Matthias Uhlig, Sigurd Schacht, Sudarshan Kamath Barkur
Large language models have gained immense importance in recent years and have demonstrated outstanding results in solving various tasks. However, despite these achievements, many q…
Towards energy-efficient Deep Learning: An overview of energy-efficient approaches along the Deep Learning Lifecycle
Vanessa Mehlin, Sigurd Schacht, Carsten Lanquillon
Deep Learning has enabled many advances in machine learning applications in the last few years. However, since current Deep Learning algorithms require much energy for computations…