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Determine the influence of each element in NLP classification tasks

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NLP Element Influence

Understanding the importance of the inputs on the output is useful across many tasks. This repository provides an information-theoretic framework to analyse the influence of inputs for text classification tasks. Natural language processing (NLP) tasks take either a single element input or multiple element inputs to predict an output variable, where an element is a block of text. Each text element has two components: an associated semantic meaning and a linguistic realization. Multiple-choice reading comprehension (MCRC) and sentiment classification (SC) are selected to showcase the framework.

If you make use of this codebase, please cite as follows: coming soon

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Determine the influence of each element in NLP classification tasks

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