Search Results for author: Zhiyuan Wen

Found 10 papers, 2 papers with code

Long Text and Multi-Table Summarization: Dataset and Method

1 code implementation8 Feb 2023 Shuaiqi Liu, Jiannong Cao, Ruosong Yang, Zhiyuan Wen

Within a report document, the salient information can be scattered in the textual and non-textual content.

Document Summarization Informativeness +1

Decode with Template: Content Preserving Sentiment Transfer

no code implementations LREC 2020 Zhiyuan Wen, Jiannong Cao, Ruosong Yang, Senzhang Wang

The two major challenges in existing works lie in (1) effectively disentangling the original sentiment from input sentences; and (2) preserving the semantic content while transferring the sentiment.

GGP: Glossary Guided Post-processing for Word Embedding Learning

no code implementations LREC 2020 Ruosong Yang, Jiannong Cao, Zhiyuan Wen

To enhance corpus based word embedding models, researchers utilize domain knowledge to learn more distinguishable representations via joint optimization and post-processing based models.

EPARS: Early Prediction of At-risk Students with Online and Offline Learning Behaviors

no code implementations6 Jun 2020 Yu Yang, Zhiyuan Wen, Jiannong Cao, Jiaxing Shen, Hongzhi Yin, Xiaofang Zhou

We propose a novel algorithm (EPARS) that could early predict STAR in a semester by modeling online and offline learning behaviors.

Management Network Embedding

Emerging App Issue Identification via Online Joint Sentiment-Topic Tracing

no code implementations23 Aug 2020 Cuiyun Gao, Jichuan Zeng, Zhiyuan Wen, David Lo, Xin Xia, Irwin King, Michael R. Lyu

Experiments on popular apps from Google Play and Apple's App Store demonstrate the effectiveness of MERIT in identifying emerging app issues, improving the state-of-the-art method by 22. 3% in terms of F1-score.

Clustering

Low-Resource Court Judgment Summarization for Common Law Systems

no code implementations7 Mar 2024 Shuaiqi Liu, Jiannong Cao, Yicong Li, Ruosong Yang, Zhiyuan Wen

Current summarization datasets are insufficient to satisfy the demands of summarizing precedents across multiple jurisdictions, especially when labeled data are scarce for many jurisdictions.

Data Augmentation

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