3 citations · 3 across the 4 of their papers we have counts for
5 papers
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,…
Grounding Natural Language Instructions: Can Large Language Models Capture Spatial Information?
Julia Rozanova, Deborah Ferreira, Krishna Dubba +3
Models designed for intelligent process automation are required to be capable of grounding user interface elements. This task of interface element grounding is centred on linking i…
Supporting Context Monotonicity Abstractions in Neural NLI Models
Julia Rozanova, Deborah Ferreira, Mokanarangan Thayaparan +2
Natural language contexts display logical regularities with respect to substitutions of related concepts: these are captured in a functional order-theoretic property called monoton…
Does My Representation Capture X? Probe-Ably
Deborah Ferreira, Julia Rozanova, Mokanarangan Thayaparan +2
Probing (or diagnostic classification) has become a popular strategy for investigating whether a given set of intermediate features is present in the representations of neural mode…
On the Evaluation of Intelligent Process Automation
Deborah Ferreira, Julia Rozanova, Krishna Dubba +2
Intelligent Process Automation (IPA) is emerging as a sub-field of AI to support the automation of long-tail processes which requires the coordination of tasks across different sys…