Papers by Adrian Cheung
Inconsistencies in Crowdsourced Slot-Filling Annotations: A Typology and Identification Methods (2020.coling-main)
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| Challenge: | Standard slot-filling models train or finetune on large datasets of carefully-annotated data that is domain specific. |
| Approach: | They propose automatic methods to identify inconsistencies in crowd-annotated data . a slot-filling model can extract the tokens "New York" as a TO LOCATION slot in a query . |
| Outcome: | The proposed methods reveal inconsistencies in data, though there is scope for improvement. |
Iterative Feature Mining for Constraint-Based Data Collection to Increase Data Diversity and Model Robustness (2020.emnlp-main)
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Stefan Larson, Anthony Zheng, Anish Mahendran, Rishi Tekriwal, Adrian Cheung, Eric Guldan, Kevin Leach, Jonathan K. Kummerfeld
| Challenge: | Recent work on dialog has found that crowdsourced data can have limited diversity as workers tend to write simple variations from prompts. |
| Approach: | They propose a general approach for guiding workers to write more diverse text by iteratively constraining their writing. |
| Outcome: | The proposed approach improves performance on dialog tasks and improves on existing datasets. |