Papers by Ouyu Lan
AlpacaTag: An Active Learning-based Crowd Annotation Framework for Sequence Tagging (P19-3)
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| Challenge: | Existing sequence annotation tools focus on improving user interfaces and user interface. |
| Approach: | They propose an open-source web-based data annotation framework for sequence tagging tasks . the framework is based on active learning and automatic crowd consolidation . |
| Outcome: | The proposed framework is a comprehensive solution for sequence labeling tasks . it can be deployed in downstream systems while new annotations are being made . |
Learning to Contextually Aggregate Multi-Source Supervision for Sequence Labeling (2020.acl-main)
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| Challenge: | Existing methods for Sequence Labeling require high-quality annotations, but imperfect annotations are relatively easy to obtain from crowdsourcing (noisy labels) Existing approaches to learn a model without knowing the underlying ground truth label sequences in the target domain are expensive and time-consuming. |
| Approach: | They propose a framework Consensus Network that can be trained on annotations from multiple sources. |
| Outcome: | The proposed framework improves on learning with crowd annotations and unsupervised cross-domain model adaptation in two practical settings. |