activity
20192026
most citedPowerGraph-LLM: Novel Power Grid Graph Embedding and Optimization with Large Language Models

24 citations · 115 across the 57 of their papers we have counts for

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Showing 2021Show all

8 papers · 1 filter

cs.SE2021★ 1 cited

A Qualitative Study on the Sources, Impacts, and Mitigation Strategies of Flaky Tests

Sarra Habchi, Guillaume Haben, Mike Papadakis +2

Test flakiness forms a major testing concern. Flaky tests manifest non-deterministic outcomes that cripple continuous integration and lead developers to investigate false alerts. I…

cs.LG2021★ 2 cited

Robust Active Learning: Sample-Efficient Training of Robust Deep Learning Models

Yuejun Guo, Qiang Hu, Maxime Cordy +2

Active learning is an established technique to reduce the labeling cost to build high-quality machine learning models. A core component of active learning is the acquisition functi…

cs.AI2021★ 1 cited

A Unified Framework for Adversarial Attack and Defense in Constrained Feature Space

Thibault Simonetto, Salijona Dyrmishi, Salah Ghamizi +2

The generation of feasible adversarial examples is necessary for properly assessing models that work in constrained feature space. However, it remains a challenging task to enforce…

cs.SE2021

Discerning Legitimate Failures From False Alerts: A Study of Chromium's Continuous Integration

Guillaume Haben, Sarra Habchi, Mike Papadakis +2

Flakiness is a major concern in Software testing. Flaky tests pass and fail for the same version of a program and mislead developers who spend time and resources investigating test…

cs.LG2021★ 1 cited

Adversarial Robustness in Multi-Task Learning: Promises and Illusions

Salah Ghamizi, Maxime Cordy, Mike Papadakis +1

Vulnerability to adversarial attacks is a well-known weakness of Deep Neural networks. While most of the studies focus on single-task neural networks with computer vision datasets,…

cs.LG2021★ 2 cited

MUTEN: Boosting Gradient-Based Adversarial Attacks via Mutant-Based Ensembles

Yuejun Guo, Qiang Hu, Maxime Cordy +2

Deep Neural Networks (DNNs) are vulnerable to adversarial examples, which causes serious threats to security-critical applications. This motivated much research on providing mechan…

cs.SE2021★ 12 cited

Automated Repair of Unrealisable LTL Specifications Guided by Model Counting

Matías Brizzio, Maxime Cordy, Mike Papadakis +3

The reactive synthesis problem consists of automatically producing correct-by-construction operational models of systems from high-level formal specifications of their behaviours.…

cs.SE2021

On the Use of Mutation in Injecting Test Order-Dependency

Sarra Habchi, Maxime Cordy, Mike Papadakis +1

Background: Test flakiness is identified as a major issue that compromises the regression testing process of complex software systems. Flaky tests manifest non-deterministic behavi…