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Seong-Whan Lee

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#artificial intelligence Preprint Oct 2026

Safeguarding Mutual Correction in Source-Free Domain Adaptation via Cut Statistics

Source-Free Domain Adaptation (SFDA) aims to adapt a source-pretrained model to an unlabeled target domain without access to the original source domain. While early single-model approaches rely on self-refinement, they are inherently susceptible to confirmation bias and struggle to correct their own systematic errors....

Seong-Whan Lee, Changhee Lee · 0 citations

Citation-Closure Retrieval and Per-Rule Attribution for Real-World Regulatory Compliance Question Answering

This work formalizes Regulatory Compliance QA with RegOps-Bench, a novel benchmark featuring an Operational Knowledge Graph derived from complex national R\&D regulations and proposes RefWalk, a unified framework driven by a shared topic anchor.

Yeong-Joon Ju, Seong-Whan Lee · 0 citations

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