As in the case of textual entailment or semantic textual similarity tasks, given pairs of sentences with a corresponding label (i.e. entailment, contradiction, neutral; or a similarity score), what would be some approaches using dgl?
One way might be to do it BERT-style and treat the sentence pair as one instance/example with a [CLS] token in the beginning, apply graph convolution using something like SegTree-Transformer, do a pooling operation to extract the CLS node vectors for classification/regression.
I would like to know what other approaches there might be for working with pairs of sentences, or more generally for sentence classification.
I’d really appreciate any thoughts!