most citedEmbedded Inter-Subject Variability in Adversarial Learning for Inertial Sensor-Based Human Activity Recognition

2 citations · 2 across the 3 of their papers we have counts for

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cs.AI2026

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…