Papers by Yongjae Lee
Shedding New Light on the Language of the Dark Web (2022.naacl-main)
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| Challenge: | Existing studies on text classification of the Dark Web have been ineffective due to its inherent characteristics. |
| Approach: | They propose a publicly available Dark Web dataset tailored towards text-based analysis. |
| Outcome: | The proposed method compares with an existing public Dark Web dataset and evaluates its suitability for various use cases. |
BitAbuse: A Dataset of Visually Perturbed Texts for Defending Phishing Attacks (2025.findings-naacl)
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| Challenge: | Phishing often targets victims through visually perturbed texts to bypass security systems . previous studies have used synthetic datasets that do not contain real-world phishing cases . |
| Approach: | They propose a visual perturbation dataset to target phishing attacks using visual perturbations. |
| Outcome: | The proposed dataset includes real-world phishing cases annotated with visual perturbations . language models trained on the proposed dataset achieved an accuracy of approximately 96% . |
Ignore Me But Don’t Replace Me: Utilizing Non-Linguistic Elements for Pretraining on the Cybersecurity Domain (2024.findings-naacl)
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| Challenge: | Existing methods to train domain expertise for cybersecurity text domains are expensive to train and run. |
| Approach: | They propose to use pretraining methods to account for non-linguistic elements in cybersecurity texts and evaluate their effectiveness through downstream tasks and probing tasks. |
| Outcome: | The proposed strategy outperforms the commonly taken approach of replacing NLEs and outperformed other cybersecurity PLMs on most tasks. |
LLM as a Risk Manager: LLM Semantic Filtering for Lead–Lag Trading in Prediction Markets (2026.acl-industry)
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Sumin Kim, Minjae Kim, Jihoon Kwon, Yoon Kim, Oscar Levy, Alejandro Lopez-Lira, Yongjae Lee, Chanyeol Choi
| Challenge: | Prediction markets provide a unique setting where event-level time series are directly tied to natural-language descriptions, yet discovering robust lead–lag relationships remains challenging due to spurious statistical correlations. |
| Approach: | They propose a statistical stage that uses Granger causality to identify candidate leader–follower pairs from market-implied probability time series and an LLM-based semantic stage that re-ranks these candidates by assessing whether the proposed direction admits a plausible economic transmission mechanism. |
| Outcome: | The proposed approach consistently outperforms the statistical baseline on Kalshi Economics markets. |
DarkBERT: A Language Model for the Dark Side of the Internet (2023.acl-long)
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| Challenge: | Recent research suggests that there are clear differences in the language used in the Dark Web compared to that of the Surface Web. |
| Approach: | They propose a language model that is pretrained on Dark Web data to combat extreme lexical diversity. |
| Outcome: | The proposed model outperforms existing models and may be useful for future research on the Dark Web. |