| Challenge: | Existing models of latent variable grammars are not observable in treebanks, so latent variables are learned using expectation-maximization. |
| Approach: | They propose a new framework that extends latent variable grammars such that each nonterminal symbol is associated with a continuous vector space representing the set of (infinitely many) subtypes of the nonterminals. |
| Outcome: | The proposed framework can achieve competitive accuracies in part-of-speech tagging and constituency parsing. |
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Transactions of the Association for Computational Linguistics, Volume 8 (2020.tacl-1)
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Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 3: System Demonstrations) (2024.acl-demos)
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Findings of the Association for Computational Linguistics: NAACL 2022 (2022.findings-naacl)
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