Papers by Ruiqing Ding

2 papers
A Unified Knowledge Graph Augmentation Service for Boosting Domain-specific NLP Tasks (2023.findings-acl)

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Challenge: Existing domain-specific pre-trained language models lack domain knowledge in domain-focused training.
Approach: They propose a unified domain language model development service to inject domain knowledge into the PLM fine-tuning stage.
Outcome: Experiments on domain-specific text classification and QA tasks verify the effectiveness and generalizability of KnowledgeDA.
DFAMS: Dynamic-flow guided Federated Alignment based Multi-prototype Search (2026.acl-long)

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Challenge: Existing methods for ambiguous queries struggle to retrieve high-quality documents . DFAMS outperforms advanced FR methods by 14.37% in knowledge classification accuracy .
Approach: They propose a framework that leverages dynamic information flow to identify latent query intents and construct semantically aligned knowledge partitions for accurate retrieval across heterogeneous sources.
Outcome: The proposed framework outperforms existing methods in classification accuracy and retrieval recall tests.

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