Corpus ID: 9895822

Semi-Markov Phrase-Based Monolingual Alignment

@inproceedings{Yao2013SemiMarkovPM,
  title={Semi-Markov Phrase-Based Monolingual Alignment},
  author={Xuchen Yao and Benjamin Van Durme and Chris Callison-Burch and P. Clark},
  booktitle={EMNLP},
  year={2013}
}
We introduce a novel discriminative model for phrase-based monolingual alignment using a semi-Markov CRF. Our model achieves stateof-the-art alignment accuracy on two phrasebased alignment datasets (RTE and paraphrase), while doing significantly better than other strong baselines in both non-identical alignment and phrase-only alignment. Additional experiments highlight the potential benefit of our alignment model to RTE, paraphrase identification and question answering, where even a naive… Expand
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43 Citations
Highly Influential Citations
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43 Citations

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Hungarian layer: A novel interpretable neural layer for paraphrase identification
  • Han Xiao
  • Medicine, Computer Science
  • Neural Networks
  • 2020
TLDR
This paper empower neural architecture with Hungarian algorithm to extract the aligned unmatched parts and applies BiLSTM/BERT to encode the input sentences into hidden representations, which outperforms other baselines, substantially and significantly. Expand
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