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This project contains the listening experiment data that was collected to study the effect of synonyms (with/without context) on word recognition in noise.

ExplainableChemTox is an innovative tool designed for the field of computational chemistry and toxicology. It leverages advanced language models to interpret molecular string representations, specifically focusing on identifying explainable chemical fragments that contribute to toxicity in various compounds.

Implementation code for the M.Sc. thesis titled 'Adversarially Learning to Manipulate the Cognitive Load of Sentences.' The code reflects the current state of the project and is subject to change.

The Generator takes 'known' data and generates 'unknown' data from that