Visual Analytics for Fine-grained Text Classification Models and Datasets

arXiv:2403.15492v1 Announce Type: new
Abstract: In natural language processing (NLP), text classification tasks are increasingly fine-grained, as datasets are fragmented into a larger number of classes that are more difficult to differentiate from one another. As a consequence, the semantic structures of datasets have become more complex, and model decisions more difficult to explain. Existing tools, suited for coarse-grained classification, falter under these additional challenges. In response to this gap, we worked closely with NLP domain experts in an iterative …

abstract analytics arxiv become classification cs.cl datasets decisions fine-grained language language processing natural natural language natural language processing nlp processing semantic tasks text text classification type visual visual analytics