2 citations · 3 across the 3 of their papers we have counts for
4 papers
The Real Cost of Context: Predicting Compute Time and Energy Consumption in LLM Prefill and Decode Phases
Lars Krupp, Daniel Geißler, Francisco M. Calatrava-Nicolas +3
The integration of Large Language Models (LLMs) into agentic architectures has substantially increased token consumption, raising concerns about their energy footprint. Yet, estima…
Quantum-inspired Embeddings Projection and Similarity Metrics for Representation Learning
Ivan Kankeu, Stefan Gerd Fritsch, Gunnar Schönhoff +3
Over the last decade, representation learning, which embeds complex information extracted from large amounts of data into dense vector spaces, has emerged as a key technique in mac…
GenAI Assisting Medical Training
Stefan Fritsch, Matthias Tschoepe, Vitor Fortes Rey +4
Medical procedures such as venipuncture and cannulation are essential for nurses and require precise skills. Learning this skill, in turn, is a challenge for educators due to the n…
MuJo: Multimodal Joint Feature Space Learning for Human Activity Recognition
Stefan Gerd Fritsch, Cennet Oguz, Vitor Fortes Rey +3
Human activity recognition (HAR) is a long-standing problem in artificial intelligence with applications in a broad range of areas, including healthcare, sports and fitness, securi…