CITATION INTENT CLASSIFIER

Technical overview

The classification part is carried out by an Ensemble Model, which is a combination of three binary classifiers and a meta classifier built on top of them.
The meta classifier carries out the voting process and returns the final classification result.
Furthermore, a threshold of 90% confidence has been defined to filter out the results on which the model is not confident enough.

Key Features

The baseline model surpass the current SOTA Macro-F1 score for the citation intent classification task with SciCite dataset.

This tool gives you the possibility to classify any number of input sentences given in input in the form of a list of tuples.
Clearly, higher the number of sentences, higher the time needed to classify all of them and to get back results.
The tool also gives you the possibility to download the results in JSON format.

Finally, you have the possibility to select one of three possible working modes:

With Sections: select this mode if ALL your sentences have also the title of the section in which the citation is contained;
Without Sections: select this mode if NONE of your sentences contains the title of the section in which the citation is, or if you want to try a classification based on the pure semantic of the sentence at hand;
Mixed: select this mode if SOME of your sentences have the title of the section in which the citation is contained, and others not. The tool will carry out the entire filtering process and return you the results.