Bilateral Multi-Perspective Matching for Natural Language Sentences

  title={Bilateral Multi-Perspective Matching for Natural Language Sentences},
  author={Zhiguo Wang and Wael Hamza and Radu Florian},
Natural language sentence matching is a fundamental technology for a variety of tasks. Previous approaches either match sentences from a single direction or only apply single granular (wordby-word or sentence-by-sentence) matching. In this work, we propose a bilateral multi-perspective matching (BiMPM) model. Given two sentences P and Q, our model first encodes them with a BiLSTM encoder. Next, we match the two encoded sentences in two directions P against Q and Q against P . In each matching… CONTINUE READING
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