My work pictured by AI – Paola Merlo
"Blackbird's language matrices (BLMs): a new task to investigate disentangled generalization in neural networks." - By Paola Merlo
What is this work about? Current successes of machine learning architectures are based on computationally expensive algorithms and prohibitively large amounts of data. We need to develop tasks and data to train networks to reach more complex and more compositional skills. In this paper, we illustrate Blackbird’s language matrices (BLMs), a novel grammatical task modelled on intelligence tests usually based on visual stimuli. The dataset is generatively constructed to support investigations of current models’ linguistic mastery and their ability to generalize them. We present the logic of the task, the method to automatically construct data on a large scale, and the architecture to learn them. Through error analysis and several experiments on variations of the dataset, we demonstrate that this language task and the data that instantiate it provide a new challenging testbed to understand generalization and abstraction.
The first word that came to mind when seeing the AI-generated picture? Goofy.
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