Papers by Yuquan Le
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. |
TermDiffuSum: A Term-guided Diffusion Model for Extractive Summarization of Legal Documents (2025.coling-main)
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| Challenge: | Recent studies have explored diffusion models for extractive summarization task, showcasing their remarkable capabilities. |
| Approach: | They propose a term-guided diffusion model for extractive summarization of legal documents that incorporates legal terminology into the model via a well-designed multifactor fusion noise weighting schedule. |
| Outcome: | The proposed model outperforms existing models on a self-constructed legal summarization dataset and achieves improvements of 3.10, 2.84, and 2.89 on three public datasets. |