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Woo-Min Song

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#artificial intelligence Preprint Oct 2026

Who's Behind the Text? Robust Model Authorship Attribution

As large language models (LLMs) are increasingly used to generate text, their misuse has become a growing societal problem, with implications for academic misconduct, model distillation, and cyberattacks. For these reasons, Model Authorship Attribution (MAA), which identifies the source model of a given text, is import...

Minseok Ko, Hyunseok Lee, Woo-Min Song et al. · 0 citations
#artificial intelligence Preprint Oct 2026

Why, Where, How: Taxonomy-guided Error Grounding for Code Repair in NL2SQL

SQL queries that large language models write from natural language questions can execute successfully yet produce incorrect results, so execution alone does not reveal what to fix. An error taxonomy says why the query is wrong, but not where to look or how to change it. Existing methods can guide SQL correction through...

Su-Chan Lee, Woo-Min Song, Hwanjo Yu et al. · 0 citations
#natural language process... Preprint Sep 2026

SGD-KV: Summarization Guided KV Cache Compression

SGD-KV (Summarization-Guided KV Cache Compression), a head-aware framework that leverages a novel chunk-summarization diagnostic task to systematically identify and prioritize attention heads specialized in hierarchical information aggregation, is presented.

Ze-Yu Liu, Woo-Min Song, Xuandi Fu et al. · 0 citations

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