Personal profile
Education
Ph.D., National Cheng Kung University,Taiwan
Courses
Deep Learning
Natural Language Processing and Applications
Natural Language Processing and Applications
Related documents
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Collaborations and top research areas from the last five years
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Projects
- 1 Active
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Research on Large Language Model Compression Techniques Based on Encoder-Decoder Heterogeneous Knowledge Distillation
Lin, Y.-J. (PI)
01/08/25 → 31/07/27
Project: National Science and Technology Council › National Science and Technology Council Academic Grants
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Automatic genetic phenotype normalization from dysmorphology physical examinations: an overview of the BioCreative VIII—Task 3 competition
Weissenbacher, D., Zhao, X., Priestley, J. R. C., Szigety, K. M., Schmidt, S. F., O'Connor, K., Soysal, E., Roberts, K., Qi, J., Luo, L., Yang, Z., Lin, H., Kim, H., Kim, C., Sohn, J., Beck, T., Rei, M., Kim, S., Simpson, T. I. & Posma, J. M. & 13 others, , 2025, In: Database. 2025, baaf051.Research output: Contribution to journal › Journal Article › peer-review
Open Access1 Scopus citations -
Exploring the Effectiveness of Pre-training Language Models with Incorporation of Diglossia for Hong Kong Content
Yung, Y. C., Lin, Y. J. & Kao, H. Y., 24 07 2025, In: ACM Transactions on Asian and Low-Resource Language Information Processing. 24, 7, 71.Research output: Contribution to journal › Journal Article › peer-review
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From Persona to Person: Enhancing the Naturalness with Multiple Discourse Relations Graph Learning in Personalized Dialogue Generation
Hsu, C. H., Lin, Y. J. & Kao, H. Y., 2025, Advances in Knowledge Discovery and Data Mining - 29th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2025, Proceedings. Wu, X., Spiliopoulou, M., Wang, C., Kumar, V., Cao, L., Wu, Y., Wu, Z. & Yao, Y. (eds.). Springer Science and Business Media Deutschland GmbH, p. 187-198 12 p. (Lecture Notes in Computer Science; vol. 15871 LNCS).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review
Open Access -
GViG: low-resource generative visual grounding using prompt-based language modeling for visual question answering
Li, Y. T., Lin, Y. J. & Kao, H. Y., 11 2025, In: International Journal of Data Science and Analytics. 20, 7, p. 6489-6505 17 p.Research output: Contribution to journal › Journal Article › peer-review
Open Access -
MAPLE: Enhancing Review Generation with Multi-Aspect Prompt LEarning in Explainable Recommendation
Yang, C. W., Feng, Z. Q., Lin, Y. J., Chen, C. W., Wu, K. D., Xu, H., Yao, J. F. & Kao, H. Y., 2025, Long Papers. Che, W., Nabende, J., Shutova, E. & Pilehvar, M. T. (eds.). Association for Computational Linguistics (ACL), p. 31803-31821 19 p. (Proceedings of the Annual Meeting of the Association for Computational Linguistics; vol. 1).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review
Open Access