Papers by Zongcheng Ji

2 papers
Enhancing Dual-Encoders with Question and Answer Cross-Embeddings for Answer Retrieval (2021.findings-emnlp)

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Challenge: Existing approaches to solve question answering (QA) problems are limited by the need for text generation and answer retrieval.
Approach: They propose to introduce QA interaction features in scoring function but at the cost of low efficiency in inference stage.
Outcome: The proposed framework significantly outperforms the state-of-the-art method on multiple answer retrieval datasets.
A Neural Transition-based Joint Model for Disease Named Entity Recognition and Normalization (2021.acl-long)

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Challenge: Existing models for disease recognition and normalization ignore text surface form of each candidate concept, causing boundary inconsistency.
Approach: They propose a neural transition-based joint model to normalize disease entities from biomedical text.
Outcome: The proposed model improves on two publicly available datasets.

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