activity
20212026
most citedOperation is the hardest teacher: estimating DNN accuracy looking for mispredictions

21 citations · 45 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CL2026

Schema-Constrained Document-Level Event Argument Extraction with Lightweight LLM Fine-Tuning

Roberto Pietrantuono, Antonio Guerriero, Pouya Sattari

Event Argument Extraction (EAE) converts documents into structured event records by identifying argument spans and assigning them schema-defined roles. Document-level EAE is challe…

cs.SE2024★ 13 cited

Causal Reasoning in Software Quality Assurance: A Systematic Review

Luca Giamattei, Antonio Guerriero, Roberto Pietrantuono +1

Context: Software Quality Assurance (SQA) is a fundamental part of software engineering to ensure stakeholders that software products work as expected after release in operation. M…

cs.SE2024★ 6 cited

DeepSample: DNN sampling-based testing for operational accuracy assessment

Antonio Guerriero, Roberto Pietrantuono, Stefano Russo

Deep Neural Networks (DNN) are core components for classification and regression tasks of many software systems. Companies incur in high costs for testing DNN with datasets represe…

cs.LG2023★ 5 cited

Iterative Assessment and Improvement of DNN Operational Accuracy

Antonio Guerriero, Roberto Pietrantuono, Stefano Russo

Deep Neural Networks (DNN) are nowadays largely adopted in many application domains thanks to their human-like, or even superhuman, performance in specific tasks. However, due to u…

cs.SE2021★ 21 cited

Operation is the hardest teacher: estimating DNN accuracy looking for mispredictions

Antonio Guerriero, Roberto Pietrantuono, Stefano Russo

Deep Neural Networks (DNN) are typically tested for accuracy relying on a set of unlabelled real world data (operational dataset), from which a subset is selected, manually labelle…