8 citations · 18 across the 11 of their papers we have counts for
5 papers · 1 filter
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,…