Papers by Fengjiao Chen

2 papers
Conjoin after Decompose: Improving Few-Shot Performance of Named Entity Recognition (2024.lrec-main)

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Challenge: Existing prompt-based NER models fail to detect entity boundaries, causing performance degradation.
Approach: They propose a model which consists of a BART encoder and a parabiotic decoder and propose ' boundary expansion strategy' to enhance the model's capability in entity type classification.
Outcome: The proposed model can achieve significant performance gains over state-of-the-art models.
Transferable and Efficient: Unifying Dynamic Multi-Domain Product Categorization (2023.acl-industry)

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Challenge: e-commerce platforms are encountering increasingly complex product categorization scenarios . multiple business domains correspond to different category taxonomies, with different depths and distinct literal expressions of category names.
Approach: They propose a taxonomy-agnostic framework that calculates semantic relatedness between product titles and category names in the vector space.
Outcome: The proposed framework outperforms strong baselineson three dynamic multi-domain product categorization tasks.

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