GAISSALabel: A tool for energy labeling of ML models
Fuente:
arXiv
Saved in:
| Main Authors: | Duran, Pau, Castaño, Joel, Gómez, Cristina, Martínez-Fernández, Silverio |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Impact of ML Optimization Tactics on Greener Pre-Trained ML Models
by: Álvarez, Alexandra González, et al.
Published: (2024)
by: Álvarez, Alexandra González, et al.
Published: (2024)
Analyzing the Evolution and Maintenance of ML Models on Hugging Face
by: Castaño, Joel, et al.
Published: (2023)
by: Castaño, Joel, et al.
Published: (2023)
Identifying architectural design decisions for achieving green ML serving
by: Durán, Francisco, et al.
Published: (2024)
by: Durán, Francisco, et al.
Published: (2024)
Lessons Learned from Mining the Hugging Face Repository
by: Castaño, Joel, et al.
Published: (2024)
by: Castaño, Joel, et al.
Published: (2024)
A Methodological Framework for LLM-Based Mining of Software Repositories
by: De Martino, Vincenzo, et al.
Published: (2025)
by: De Martino, Vincenzo, et al.
Published: (2025)
A Framework for Using LLMs for Repository Mining Studies in Empirical Software Engineering
by: de Martino, Vincenzo, et al.
Published: (2024)
by: de Martino, Vincenzo, et al.
Published: (2024)
Do Developers Adopt Green Architectural Tactics for ML-Enabled Systems? A Mining Software Repository Study
by: De Martino, Vincenzo, et al.
Published: (2024)
by: De Martino, Vincenzo, et al.
Published: (2024)
Green Architectural Tactics in ML-enabled Systems: An LLM-based Repository Mining Study
by: De Martino, Vincenzo, et al.
Published: (2026)
by: De Martino, Vincenzo, et al.
Published: (2026)
How do Machine Learning Models Change?
by: Castaño, Joel, et al.
Published: (2024)
by: Castaño, Joel, et al.
Published: (2024)
Insights into resource utilization of code small language models serving with runtime engines and execution providers
by: Durán, Francisco, et al.
Published: (2024)
by: Durán, Francisco, et al.
Published: (2024)
Energy Consumption of Automated Program Repair
by: Martinez, Matias, et al.
Published: (2022)
by: Martinez, Matias, et al.
Published: (2022)
SEMODS: A Validated Dataset of Open-Source Software Engineering Models
by: González, Alexandra, et al.
Published: (2026)
by: González, Alexandra, et al.
Published: (2026)
Towards a Classification of Open-Source ML Models and Datasets for Software Engineering
by: González, Alexandra, et al.
Published: (2024)
by: González, Alexandra, et al.
Published: (2024)
A Tool for Automatically Cataloguing and Selecting Pre-Trained Models and Datasets for Software Engineering
by: González, Alexandra, et al.
Published: (2026)
by: González, Alexandra, et al.
Published: (2026)
Guiding the retraining of convolutional neural networks against adversarial inputs
by: López, Francisco Durán, et al.
Published: (2022)
by: López, Francisco Durán, et al.
Published: (2022)
MLScent A tool for Anti-pattern detection in ML projects
by: Shivashankar, Karthik, et al.
Published: (2025)
by: Shivashankar, Karthik, et al.
Published: (2025)
ARENA: A tool for measuring and analysing the energy efficiency of Android apps
by: Anwar, Hina
Published: (2025)
by: Anwar, Hina
Published: (2025)
Innovating for Tomorrow: The Convergence of SE and Green AI
by: Cruz, Luís, et al.
Published: (2024)
by: Cruz, Luís, et al.
Published: (2024)
Exploring the Role of Women in Hugging Face Organizations
by: Salinas, Maria Tubella, et al.
Published: (2025)
by: Salinas, Maria Tubella, et al.
Published: (2025)
Estimating Deep Learning energy consumption based on model architecture and training environment
by: del Rey, Santiago, et al.
Published: (2023)
by: del Rey, Santiago, et al.
Published: (2023)
Cataloguing Hugging Face Models to Software Engineering Activities: Automation and Findings
by: González, Alexandra, et al.
Published: (2025)
by: González, Alexandra, et al.
Published: (2025)
Proto-ML: An IDE for ML Solution Prototyping
by: Coban, Selin, et al.
Published: (2026)
by: Coban, Selin, et al.
Published: (2026)
Addressing Quality Challenges in Deep Learning: The Role of MLOps and Domain Knowledge
by: del Rey, Santiago, et al.
Published: (2025)
by: del Rey, Santiago, et al.
Published: (2025)
Performance Smells in ML and Non-ML Python Projects: A Comparative Study
by: Belias, François, et al.
Published: (2025)
by: Belias, François, et al.
Published: (2025)
Buggin: Automatic intrinsic bugs classification model using NLP and ML
by: Bhandari, Pragya, et al.
Published: (2025)
by: Bhandari, Pragya, et al.
Published: (2025)
Aggregating empirical evidence from data strategy studies: a case on model quantization
by: del Rey, Santiago, et al.
Published: (2025)
by: del Rey, Santiago, et al.
Published: (2025)
Enhancing a gamified tool for UML modeling education
by: Garaccione, Giacomo, et al.
Published: (2026)
by: Garaccione, Giacomo, et al.
Published: (2026)
What do AI/ML practitioners think about AI/ML bias?
by: Pant, Aastha, et al.
Published: (2024)
by: Pant, Aastha, et al.
Published: (2024)
EasyRpl: A web-based tool for modelling and analysis of cross-organisational workflows
by: Ali, Muhammad Rizwan, et al.
Published: (2025)
by: Ali, Muhammad Rizwan, et al.
Published: (2025)
From OCL to JSX: declarative constraint modeling in modern SaaS tools
by: Bucchiarone, Antonio, et al.
Published: (2025)
by: Bucchiarone, Antonio, et al.
Published: (2025)
Self-Admitted Technical Debt in LLM Software: An Empirical Comparison with ML and Non-ML Software
by: Selvanayagam, Niruthiha, et al.
Published: (2026)
by: Selvanayagam, Niruthiha, et al.
Published: (2026)
The More the Merrier? Navigating Accuracy vs. Energy Efficiency Design Trade-Offs in Ensemble Learning Systems
by: Omar, Rafiullah, et al.
Published: (2024)
by: Omar, Rafiullah, et al.
Published: (2024)
A quantitative framework for evaluating architectural patterns in ML systems
by: Emanuilov, Simeon, et al.
Published: (2025)
by: Emanuilov, Simeon, et al.
Published: (2025)
Uncertainty Modeling for SysML v2
by: Zhang, Man, et al.
Published: (2026)
by: Zhang, Man, et al.
Published: (2026)
ICVul: A Well-labeled C/C++ Vulnerability Dataset with Comprehensive Metadata and VCCs
by: Lu, Chaomeng, et al.
Published: (2025)
by: Lu, Chaomeng, et al.
Published: (2025)
MOTIF: A tool for Mutation Testing with Fuzzing
by: Lee, Jaekwon, et al.
Published: (2024)
by: Lee, Jaekwon, et al.
Published: (2024)
Ensuring Robustness in ML-enabled Software Systems: A User Survey
by: Abdelkader, Hala, et al.
Published: (2025)
by: Abdelkader, Hala, et al.
Published: (2025)
Error Understanding in Program Code With LLM-DL for Multi-label Classification
by: Amin, Md Faizul Ibne, et al.
Published: (2026)
by: Amin, Md Faizul Ibne, et al.
Published: (2026)
Contextual Fairness-Aware Practices in ML: A Cost-Effective Empirical Evaluation
by: Parziale, Alessandra, et al.
Published: (2025)
by: Parziale, Alessandra, et al.
Published: (2025)
A Comprehensive Multi-Vocal Empirical Study of ML Cloud Service Misuses
by: Amor, Hadil Ben, et al.
Published: (2025)
by: Amor, Hadil Ben, et al.
Published: (2025)
Similar Items
-
Impact of ML Optimization Tactics on Greener Pre-Trained ML Models
by: Álvarez, Alexandra González, et al.
Published: (2024) -
Analyzing the Evolution and Maintenance of ML Models on Hugging Face
by: Castaño, Joel, et al.
Published: (2023) -
Identifying architectural design decisions for achieving green ML serving
by: Durán, Francisco, et al.
Published: (2024) -
Lessons Learned from Mining the Hugging Face Repository
by: Castaño, Joel, et al.
Published: (2024) -
A Methodological Framework for LLM-Based Mining of Software Repositories
by: De Martino, Vincenzo, et al.
Published: (2025)