Papers with inference models
pair2vec: Compositional Word-Pair Embeddings for Cross-Sentence Inference (N19-1)
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| Challenge: | Existing inference models that rely heavily on unsupervised single-word embeddings struggle to learn implied relationships between pairs of words. |
| Approach: | They propose to use word embeddings to learn and use background knowledge about implied relationships between words that are crucial for cross-sentence inference problems. |
| Outcome: | The proposed models gain 2.7% on the recently released SQuAD 2.0 and 1.3% on MultiNLI, and 8.8% on the adversarial SQu AD datasets. |