Research Highlights

  • arXiv'25 / RegexPSPACE: A Benchmark for Evaluating LLM Reasoning on PSPACE-Complete Regex Problems / GitHub / summary / 요약
  • arXiv'25 / ECO: Enhanced Code Optimization via Performance-Aware Prompting / GitHub / 요약
  • arXiv'25 / Do Large Language Models Respect Contracts? Evaluating and Enforcing Contract-Adherence in Code Generation / GitHub / 요약
  • arXiv'25 / A Linguistics-Aware LLM Watermarking via Syntactic Predictability / GitHub / 요약
  • arXiv'25 / DITTO: A Spoofing Attack Framework on Watermarked LLMs via Knowledge Distillation / GitHub / 요약
  • arXiv'25 / RV-HATE: Reinforce Multi-Module Voting for Implicit Hate Speech Detection / GitHub / 요약
  • arXiv'25 / KOTOX: A Korean Toxic Dataset for Deobfuscation and Detoxification / GitHub / 요약
  • arXiv'25 / Reparing Regex Vuilnerabilities via Localization-Guided Instructions / GitHub / 요약
  • arXiv'25 / MEC^3O: Multi-Expert Consensus for Code Time Complexity Prediction / GitHub / 요약
  • arXiv'25 / Marking Code Without Breaking It: Code Watermarking for Detecting LLM-Generated Code / GitHub / 요약
  • EMNLP'25 / AmpleHate: Amplifying the Attention for Versatile Implicit Hate Detection / GitHub / 요약
  • EMNLP-Findings'25 / TrapDoc: Deceiving LLM Users by Injecting Imperceptible Phantom Tokens into Documents / GitHub / 요약
  • EMNLP-Findings'25 / CodeComplex: Dataset for the Worst-Case Time Complexity Prediction / GitHub / summary / 요약
  • IJCAI'25 / LogiCase: Effective Test Case Generation from Logical Description in Competitive Programming / GitHub / 요약
  • NAACL'25 / TCProF: Time-Complexity Prediction SSL Framework / GitHub / summary / 요약
  • ACL'25 / KatFishNet: Detecting LLM-Generated Korean Text through Linguistic Feature Analysis / GitHub / 요약
  • arXiv'25 / Detection of LLM-Paraphrased Code and Identification of the Responsible LLM Using Coding Style Features / GitHub / 요약
  • arXiv'25 / URECA: The Chain of Two Minimum Set Cover Problems exists behind Adaptation to Shifts in Semantic Code Search / 요약
  • Coling'25 / Analyzing Offensive Language Dataset Insights from Training Dynamics and Human Agreement Level / GitHub / 요약


    NEWS

  • 연구실에 지원할 학생들은 모집주제 페이지를 먼저 확인해주세요.
  • We have four papers accepted for EMNLP 2025; two for main, two for findings. Congrats to all co-authors!
  • We have one paper (Pattern Mining under Simon's Congruence) accepted for DLT 2025, which will be held in Korea for the first time! Congrats, Sungmin.
  • We have one paper (KatFishNet: Detecting LLM-Generated Korean Text through Linguistic Feature Analysis) accpeted for ACL 2025. Well done, Shinwoo, Shubin, Do-Kyung---especially, Shubin was an undergrad intern in our lab, AMAZING!
  • Our "LogiCase: Effective Test Case Generation from Logical Description in Competitive Programming " paper is accepted for IJCAI 2025. Good job, Sicheol. This is joint work with Prof. Sang-Ki Ko's group from University of Seoul.
  • Our "TCProF: Time-Complexity Prediction SSL Framework" paper is accepted for NAACL 2025. A more detail info will be updated soon. Congrats Joonghyuk, Hyeseon, Jungin and Soohan.
  • Our "Impact of Large Language Models of Code on Fault Localization" paper is accepted for ICST 2025. This is joint work with Prof. Hyeonseung Im's group from Kangwon National University.
  • Our "Analyzing Offensive Language Dataset Insights from Training Dynamics and Human Agreement Level" paper is accepted for COLING 2025. Congrats Do-Kyung and Hyeseon.


    RESEARCH INTERESTS


    Contact Information
    School of Computing, Yonsei University
    50 Yonsei-Ro, Seodaemun-Gu, Seoul 03722, Republic of Korea
    Email: emmous [at] yonsei [dot] ac [dot] kr

    Last updated 2025/4/8