Papers by Gyuseong Lee

3 papers
Thunder-NUBench: A Benchmark for LLMs’ Sentence-Level Negation Understanding (2026.findings-eacl)

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Challenge: Negation is a fundamental linguistic phenomenon that poses ongoing challenges for Large Language Models (LLMs) Current benchmarks treat negation as a minor detail within broader tasks, such as natural language inference.
Approach: They propose a novel benchmark specifically created to assess sentence-level understanding of negation in Large Language Models (LLMs).
Outcome: The proposed benchmark compares standard negation with structurally diverse alternatives, such as local negation, contradiction, and paraphrase.
Assessing Socio-Cultural Alignment and Technical Safety of Sovereign LLMs (2025.findings-emnlp)

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Challenge: Recent trends in LLMs development show growing interest in the use and application of sovereign LLM models.
Approach: They propose a framework for extracting and evaluating socio-cultural elements of sovereign LLMs and assess their technical robustness.
Outcome: The proposed framework assesses the socio-cultural elements of sovereign LLMs and their technical robustness.
Thunder-DeID: Accurate and Efficient De-identification Framework for Korean Court Judgments (2025.findings-emnlp)

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Challenge: a recent study shows that the current de-identification process is inadequate for court judgments at scale .
Approach: They propose a framework for de-identification that aligns with relevant laws and practices . they construct and release the first Korean legal dataset containing annotated judgments .
Outcome: The proposed framework achieves state-of-the-art in the de-identification of court judgments.

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