Personal profile
In Korean
이성현 교수(IT대학 컴퓨터학부)
Education
(2024) Ph.D., POSTECH
(2018) B.S., POSTECH
(2018) B.S., POSTECH
Professional Experience
(2024) Postdoctoral Researcher, POSTECH
(2021-2024) ScatterLab Inc
(2021-2024) ScatterLab Inc
Research Interests
Large Language Models
Code Generation
Language Model Evaluation
Natural Language Processing
Code Generation
Language Model Evaluation
Natural Language Processing
Major Research Achievements
o Eliciting Instruction-tuned Code Language Models' Capabilities to Utilize Auxiliary Function for Code Generation (EMNLP24 FIndings)
o Exploring Language Model’s Code Generation Ability with Auxiliary Functions (NAACL24 Findings)
o KoDialogBench: Evaluating Conversational Understanding of Language Models with Korean Dialogue Benchmark (COLING24)
o Toward Interpretable Semantic Textual Similarity via Optimal Transport-based Contrastive Sentence Learning (ACL22)
o OoMMix: Out-of-manifold Regularization in Contextual Embedding Space for Text Classification (ACL21)
o BHIN2vec: Balancing the Type of Relations in Heterogeneous Information Network (CIKM19)
o Exploring Language Model’s Code Generation Ability with Auxiliary Functions (NAACL24 Findings)
o KoDialogBench: Evaluating Conversational Understanding of Language Models with Korean Dialogue Benchmark (COLING24)
o Toward Interpretable Semantic Textual Similarity via Optimal Transport-based Contrastive Sentence Learning (ACL22)
o OoMMix: Out-of-manifold Regularization in Contextual Embedding Space for Text Classification (ACL21)
o BHIN2vec: Balancing the Type of Relations in Heterogeneous Information Network (CIKM19)
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Collaborations and top research areas from the last five years
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Accelerating Sequential Pattern Mining on Spark: A SPADE-Based Approach
Park, Y. & Lee, S., Feb 2026, In: IEICE Transactions on Information and Systems. E109.D, 2, p. 273-278 6 p.Research output: Contribution to journal › Article › peer-review
Open Access -
Minimizing Response Latency in LLM-Based Agent Systems: A Comprehensive Survey
Park, G., Lee, S. & Park, Y., 2026, In: IEEE Access. 14, p. 26140-26168 29 p.Research output: Contribution to journal › Review article › peer-review
Open Access -
How Diversely Can Language Models Solve Problems? Exploring the Algorithmic Diversity of Model-Generated Code
Lee, S., Chon, H., Jang, J., Lee, D. & Yu, H., 2025, EMNLP 2025 - 2025 Conference on Empirical Methods in Natural Language Processing, Findings of EMNLP 2025. Christodoulopoulos, C., Chakraborty, T., Rose, C. & Peng, V. (eds.). Association for Computational Linguistics (ACL), p. 152-167 16 p. (EMNLP 2025 - 2025 Conference on Empirical Methods in Natural Language Processing, Findings of EMNLP 2025).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review
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Verbosity-Aware Rationale Reduction: Sentence-Level Rationale Reduction for Efficient and Effective Reasoning
Jang, J., Kim, J., Kweon, W., Lee, S. & Yu, H., 2025, Findings of the Association for Computational Linguistics: ACL 2025. Che, W., Nabende, J., Shutova, E. & Pilehvar, M. T. (eds.). Association for Computational Linguistics (ACL), p. 20769-20784 16 p. (Proceedings of the Annual Meeting of the Association for Computational Linguistics).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review
Open Access -
Eliciting Instruction-tuned Code Language Models' Capabilities to Utilize Auxiliary Function for Code Generation
Lee, S., Kim, S., Jang, J., Chon, H., Lee, D. & Yu, H., 2024, EMNLP 2024 - 2024 Conference on Empirical Methods in Natural Language Processing, Findings of EMNLP 2024. Al-Onaizan, Y., Bansal, M. & Chen, Y.-N. (eds.). Association for Computational Linguistics (ACL), p. 1840-1846 7 p. (EMNLP 2024 - 2024 Conference on Empirical Methods in Natural Language Processing, Findings of EMNLP 2024).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review
Open Access