Cover Image

Toward Systematic Counterfactual Fairness Evaluation of Large Language Models: The CAFFE Framework

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Parziale, Alessandra, Voria, Gianmario, Pontillo, Valeria, Catolino, Gemma, De Lucia, Andrea, Palomba, Fabio
Format:	Preprint
Published:	2025
Subjects:	Software Engineering
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

SCOPE: A Dataset of Stereotyped Prompts for Counterfactual Fairness Assessment of LLMs
by: Parziale, Alessandra, et al.
Published: (2026)

Contextual Fairness-Aware Practices in ML: A Cost-Effective Empirical Evaluation
by: Parziale, Alessandra, et al.
Published: (2025)

Bias Ahead: Sensitive Prompts as Early Warnings for Fairness in Large Language Models
by: Voria, Gianmario, et al.
Published: (2026)

Once Upon a Team: Investigating Bias in LLM-Driven Software Team Composition and Task Allocation
by: Parziale, Alessandra, et al.
Published: (2026)

RECOVER: Toward Requirements Generation from Stakeholders' Conversations
by: Voria, Gianmario, et al.
Published: (2024)

From Expectation to Habit: Why Do Software Practitioners Adopt Fairness Toolkits?
by: Voria, Gianmario, et al.
Published: (2024)

Data Preparation for Fairness-Performance Trade-Offs: A Practitioner-Friendly Alternative?
by: Voria, Gianmario, et al.
Published: (2024)

Tracing Stereotypes in Pre-trained Transformers: From Biased Neurons to Fairer Models
by: Voria, Gianmario, et al.
Published: (2026)

A Catalog of Fairness-Aware Practices in Machine Learning Engineering
by: Voria, Gianmario, et al.
Published: (2024)

Investigating the Role of Cultural Values in Adopting Large Language Models for Software Engineering
by: Lambiase, Stefano, et al.
Published: (2024)

Motivations, Challenges, Best Practices, and Benefits for Bots and Conversational Agents in Software Engineering: A Multivocal Literature Review
by: Lambiase, Stefano, et al.
Published: (2024)

How Do Communities of ML-Enabled Systems Smell? A Cross-Sectional Study on the Prevalence of Community Smells
by: Annunziata, Giusy, et al.
Published: (2025)

Exploring Individual Factors in the Adoption of LLMs for Specific Software Engineering Purposes
by: Lambiase, Stefano, et al.
Published: (2025)

Classification, Challenges, and Automated Approaches to Handle Non-Functional Requirements in ML-Enabled Systems: A Systematic Literature Review
by: De Martino, Vincenzo, et al.
Published: (2023)

Socio-Technical Well-Being of Quantum Software Communities: An Overview on Community Smells
by: Lambiase, Stefano, et al.
Published: (2026)

GenFair: Systematic Test Generation for Fairness Fault Detection in Large Language Models
by: Srinivasan, Madhusudan, et al.
Published: (2025)

On the Robustness of Fairness Practices: A Causal Framework for Systematic Evaluation
by: Monjezi, Verya, et al.
Published: (2026)

A Methodological Framework for LLM-Based Mining of Software Repositories
by: De Martino, Vincenzo, et al.
Published: (2025)

LLM-Assisted Empirical Software Engineering: Systematic Literature Review and Research Agenda
by: Gomes, Victoria, et al.
Published: (2026)

REST in Pieces: RESTful Design Rule Violations in Student-Built Web Apps
by: Di Meglio, Sergio, et al.
Published: (2025)

Do Developers Adopt Green Architectural Tactics for ML-Enabled Systems? A Mining Software Repository Study
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)

Advances in Artificial Intelligence forDiabetes Prediction: Insights from a Systematic Literature Review
by: Khokhar, Pir Bakhsh, et al.
Published: (2024)

Investigating the Performance of Small Language Models in Detecting Test Smells in Manual Test Cases
by: Lucas, Keila, et al.
Published: (2025)

Meta-Fair: AI-Assisted Fairness Testing of Large Language Models
by: Romero-Arjona, Miguel, et al.
Published: (2025)

A First Look at the Lifecycle of DL-Specific Self-Admitted Technical Debt
by: Recupito, Gilberto, et al.
Published: (2025)

Investigating Technical Debt Types, Issues, and Solutions in Serverless Computing
by: Perera, Hasini Sumalee, et al.
Published: (2026)

A Framework for Using LLMs for Repository Mining Studies in Empirical Software Engineering
by: de Martino, Vincenzo, et al.
Published: (2024)

Towards Fair Machine Learning Software: Understanding and Addressing Model Bias Through Counterfactual Thinking
by: Wang, Zichong, et al.
Published: (2023)

Towards Systematic Specification and Verification of Fairness Requirements: A Position Paper
by: Ramadan, Qusai, et al.
Published: (2025)

Towards Understanding Bugs in Distributed Training and Inference Frameworks for Large Language Models
by: Yu, Xiao, et al.
Published: (2025)

A Systematic Mapping on Software Fairness: Focus, Trends and Industrial Context
by: Nepomuceno, Kessia, et al.
Published: (2025)

Fairness Mediator: Neutralize Stereotype Associations to Mitigate Bias in Large Language Models
by: Xiao, Yisong, et al.
Published: (2025)

Towards Automated Page Object Generation for Web Testing using Large Language Models
by: Karagöz, Betül, et al.
Published: (2026)

In Search of Metrics to Guide Developer-Based Refactoring Recommendations
by: Robredo, Mikel, et al.
Published: (2024)

STELLAR: A Search-Based Testing Framework for Large Language Model Applications
by: Sorokin, Lev, et al.
Published: (2026)

Do Prompt Patterns Affect Code Quality? A First Empirical Assessment of ChatGPT-Generated Code
by: Della Porta, Antonio, et al.
Published: (2025)

Testing Framework Migration with Large Language Models
by: Alves, Altino, et al.
Published: (2026)

Towards Transparent and Accurate Diabetes Prediction Using Machine Learning and Explainable Artificial Intelligence
by: Khokhar, Pir Bakhsh, et al.
Published: (2025)

Large Language Models for Unit Testing: A Systematic Literature Review
by: Zhang, Quanjun, et al.
Published: (2025)