no code implementations • 26 Aug 2020 • Guy Clarke Marshall, Caroline Jay, André Freitas
We utilise Richards-Engelhardt framework as a tool for understanding Natural Language Processing systems diagrams.
no code implementations • 28 Aug 2020 • Guy Clarke Marshall, André Freitas, Caroline Jay
Neural networks are a prevalent and effective machine learning component, and their application is leading to significant scientific progress in many domains.
no code implementations • ICLR Workshop Rethinking_ML_Papers 2021 • Guy Clarke Marshall, Caroline Jay, André Freitas
This paper advocates for diagrammatic summary publications for machine learning system architecture papers.
no code implementations • 30 Apr 2021 • Guy Clarke Marshall, Caroline Jay, Andre Freitas
We analyse a corpus of diagrams found in scholarly computational linguistics conference proceedings (ACL 2017), and find inclusion of a system diagram to be correlated with higher numbers of citations after 3 years.
no code implementations • 30 Apr 2021 • Guy Clarke Marshall, Caroline Jay, Andre Freitas
Perhaps because of this, diagrams, as "icons of relation", are a prevalent medium for signifying complex models.
no code implementations • 30 Apr 2021 • Guy Clarke Marshall, Caroline Jay, Andre Freitas
Using a corpus-based approach, we argue that the heterogeneous diagrammatic notations used for neural network systems has implications for signification in this domain.