1 citations · 2 across the 9 of their papers we have counts for
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VERA: A Responsible AI Dashboard for Assessing LLM Deployments in Light of the EU AI Act
Robin Quériaux, Solveig Bachellery, Léa Déléris +4
Institutions that deploy large language models in regulated settings often need technical evidence of responsible AI practices before approving a deployment. COMPL-AI provides a te…
Beyond the Need for Speed: Energy-Aware Code Generation via Simulation-Guided Reinforcement Learning
Saurabhsingh Rajput, Tushar Sharma
Code models strictly prioritize functional correctness, leaving software energy efficiency as an unoptimized byproduct. Training models to generate energy-efficient code requires r…
Hierarchical Fault Detection and Diagnosis for Transformer Architectures
Sigma Jahan, Saurabh Singh Rajput, Tushar Sharma +1
Transformers now underpin critical AI systems across industry and research. Yet their faults can silently alter model behavior without runtime errors, and existing techniques offer…
Watts This Smell: A Comprehensive Taxonomy of Software Energy Smells
Mohammadjavad Mehditabar, Saurabhsingh Rajput, Tushar Sharma
As software proliferates across domains, its aggregate energy footprint has become a major concern. To reduce software's growing environmental footprint, developers need to identif…
CodeGreen: Towards Improving Precision and Portability in Software Energy Measurement
Saurabhsingh Rajput, Tushar Sharma
Accurate software energy measurement is critical for optimizing energy, yet existing profilers force a trade-off between measurement accuracy and overhead due to tight coupling wit…
Energy Flow Graph: Modeling Software Energy Consumption
Saurabhsingh Rajput, Tushar Sharma
The growing energy demands of computational systems necessitate a fundamental shift from performance-centric design to one that treats energy consumption as one of the primary desi…
FlipFlop: A Static Analysis-based Energy Optimization Framework for GPU Kernels
Saurabhsingh Rajput, Alexander Brandt, Vadim Elisseev +1
Artificial Intelligence (AI) applications, such as Large Language Models, are primarily driven and executed by Graphics Processing Units (GPUs). These GPU programs (kernels) consum…