Papers by Michael Hammond
Automatic Correction of Syntactic Dependency Annotation Differences (2022.lrec-1)
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| Challenge: | Annotation inconsistencies between data sets can cause problems for low-resource NLP . a simple method for automatically detecting annotation mismatches between corpora is proposed . |
| Approach: | They propose a method for automatically detecting annotation mismatches between dependency parsing corpora . they also propose three related methods for automatically configuring the mismatch . |
| Outcome: | The proposed method improves performance on both converted and unconverted data. |
PyFoma: a Python finite-state compiler module (2024.acl-demos)
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| Challenge: | Finite-state models can be used to constrain output of neural networks to prevent text generation that fails to adhere to a specific format. |
| Approach: | They propose to build finite-state automata from regular expressions, string rewriting rules, right-linear grammars, or low-level state/transition manipulation. |
| Outcome: | The module is designed for teaching finite-state models and finite models. |