8 citations · 18 across the 11 of their papers we have counts for
11 papers
LF-checker: Machine Learning Acceleration of Bounded Model Checking for Concurrency Verification (Competition Contribution)
Tong Wu, Edoardo Manino, Fatimah Aljaafari +2
We describe and evaluate LF-checker, a metaverifier tool based on machine learning. It extracts multiple features of the program under test and predicts the optimal configuration (…
Montague semantics and modifier consistency measurement in neural language models
Danilo S. Carvalho, Edoardo Manino, Julia Rozanova +2
This work proposes a novel methodology for measuring compositional behavior in contemporary language embedding models. Specifically, we focus on adjectival modifier phenomena in ad…
Towards Global Neural Network Abstractions with Locally-Exact Reconstruction
Edoardo Manino, Iury Bessa, Lucas Cordeiro
Neural networks are a powerful class of non-linear functions. However, their black-box nature makes it difficult to explain their behaviour and certify their safety. Abstraction te…
CEG4N: Counter-Example Guided Neural Network Quantization Refinement
João Batista P. Matos, Iury Bessa, Edoardo Manino +2
Neural networks are essential components of learning-based software systems. However, their high compute, memory, and power requirements make using them in low resources domains ch…
Combining BMC and Fuzzing Techniques for Finding Software Vulnerabilities in Concurrent Programs
Fatimah K. Aljaafari, Rafael Menezes, Edoardo Manino +3
Finding software vulnerabilities in concurrent programs is a challenging task due to the size of the state-space exploration, as the number of interleavings grows exponentially wit…
Systematicity, Compositionality and Transitivity of Deep NLP Models: a Metamorphic Testing Perspective
Edoardo Manino, Julia Rozanova, Danilo Carvalho +2
Metamorphic testing has recently been used to check the safety of neural NLP models. Its main advantage is that it does not rely on a ground truth to generate test cases. However,…
QNNVerifier: A Tool for Verifying Neural Networks using SMT-Based Model Checking
Xidan Song, Edoardo Manino, Luiz Sena +5
QNNVerifier is the first open-source tool for verifying implementations of neural networks that takes into account the finite word-length (i.e. quantization) of their operands. The…
Verifying Quantized Neural Networks using SMT-Based Model Checking
Luiz Sena, Xidan Song, Erickson Alves +4
Artificial Neural Networks (ANNs) are being deployed for an increasing number of safety-critical applications, including autonomous cars and medical diagnosis. However, concerns ab…
Zealotry and Influence Maximization in the Voter Model: When to Target Zealots?
Guillermo Romero Moreno, Edoardo Manino, Long Tran-Thanh +1
In this paper, we study influence maximization in the voter model in the presence of biased voters (or zealots) on complex networks. Under what conditions should an external contro…
Streaming Bayesian Inference for Crowdsourced Classification
Edoardo Manino, Long Tran-Thanh, Nicholas R. Jennings
A key challenge in crowdsourcing is inferring the ground truth from noisy and unreliable data. To do so, existing approaches rely on collecting redundant information from the crowd…
Efficiency of active learning for the allocation of workers on crowdsourced classification tasks
Edoardo Manino, Long Tran-Thanh, Nicholas R. Jennings
Crowdsourcing has been successfully employed in the past as an effective and cheap way to execute classification tasks and has therefore attracted the attention of the research com…