Jiewen Wu


2021

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Analyzing Code Embeddings for Coding Clinical Narratives
Wei Shi | Jiewen Wu | Xiwen Yang | Nancy Chen | Ivan Ho Mien | Jung-Jae Kim | Pavitra Krishnaswamy
Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021

2018

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Attention-based Semantic Priming for Slot-filling
Jiewen Wu | Rafael E. Banchs | Luis Fernando D’Haro | Pavitra Krishnaswamy | Nancy Chen
Proceedings of the Seventh Named Entities Workshop

The problem of sequence labelling in language understanding would benefit from approaches inspired by semantic priming phenomena. We propose that an attention-based RNN architecture can be used to simulate semantic priming for sequence labelling. Specifically, we employ pre-trained word embeddings to characterize the semantic relationship between utterances and labels. We validate the approach using varying sizes of the ATIS and MEDIA datasets, and show up to 1.4-1.9% improvement in F1 score. The developed framework can enable more explainable and generalizable spoken language understanding systems.