Experiments on sentence modeling with zero-context (sentiment analysis), singlecontext (textual entailment) and multiplecontext (claim verification) demonstrate the effectiveness of ATTCONV in sentence representation learning with the incorporation of context.
attentive convolution outperforms attentive pooling and is a strong competitor to popular attentive RNNs.