Papers by Ying Wenjie

3 papers
BCTH: A Novel Text Hashing Approach via Bayesian Clustering (2020.aacl-main)

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Challenge: Similarity search is a promising strategy to find the most similar items for a given query item.
Approach: They propose to utilize Bayesian Clustering for Text Hashing to map documents to binary codes by utilizing multiple Bayessian Clusters in parallel.
Outcome: The proposed approach is competitive compared with baselines in the perspective of precision and training speed.
Empowering Tabular Data Preparation with Language Models: Why and How? (2026.acl-long)

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Challenge: Tabular data preparation is a critical step in enhancing the usability of tabular data.
Approach: They analyze how LMs can be combined with other components for different tabular data preparation tasks.
Outcome: The proposed methods lack the ability to capture the relationships within tables and adapt to the tasks involved.
Agent-based Substructure Counting under Local Differential Privacy (2026.acl-long)

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Challenge: Recent studies have demonstrated the ability of Large Language Models (LLMs) to process graph problems.
Approach: They propose to decompose substructure counting into node-level tasks distributed among node agents and embed the knowledge of distributed algorithms and DP frameworks in the curator agent and privacy controller.
Outcome: Extensive experiments on 6 real-world datasets validate the effectiveness of the proposed framework for substructure counting tasks under edge local differential privacy (LDP).

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