Bag-of-Words vs. Sequence vs. Graph vs. Hierarchy for Single- and Multi-Label Text Classification. (arXiv:2204.03954v1 [cs.CL])

Graph neural networks have triggered a resurgence of graph-based text
classification methods, defining today's state of the art. We show that a
simple multi-layer perceptron (MLP) using a Bag of Words (BoW) outperforms the
recent graph-based models TextGCN and HeteGCN in an inductive text
classification setting and is comparable with HyperGAT in single-label
classification. We also run our own experiments on multi-label classification,
where the simple MLP outperforms the recent sequential-based gMLP and aMLP
models. Moreover, we fine-tune a sequence-based …

arxiv bag classification graph text text classification words