Papers by Emily Goodwin
Synth-SBDH: A Synthetic Dataset of Social and Behavioral Determinants of Health for Clinical Text (2025.emnlp-main)
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| Challenge: | Existing SBDH datasets lack detailed annotations and are limited in their availability and coverage. |
| Approach: | They propose a synthetic SBDH annotation dataset with detailed SBDH status, temporal information, and rationale across 15 categories. |
| Outcome: | The proposed dataset outperforms models with no Synth-SBDH training on three tasks using real-world clinical datasets from two distinct hospital settings. |
Probing Linguistic Systematicity (2020.acl-main)
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| Challenge: | Existing evidence that deep natural language understanding models do not learn systematically is lacking. |
| Approach: | They examine whether deep natural language understanding models exhibit systematicity . they find that network architectures can generalize non-systematically . |
| Outcome: | The proposed model generalizes non-systematically, but is unsatisfactory, the authors argue . they show that the current state-of-the-art models do not generalize systematically . |
Compositional Generalization in Dependency Parsing (2022.acl-long)
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| Challenge: | Compositionality is the ability to combine familiar units like words into novel phrases and sentences. |
| Approach: | They introduce a set of dependency parses for Compositional Freebase Queries (CFQ) they analyze the behaviour of a state-of-the-art dependency parser on the CFQ dataset . |
| Outcome: | The proposed dependency parser performs lower on the most challenging splits with the highest compound divergence. |