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This paper refines word-based grammatical error annotation for L2 Korean by addressing problems in existing resources, including surface target realization and single-reference evaluation, and demonstrates improvements using KoBART-based correction.
NVIDIA's Nemotron-Personas-Korea is a dataset of 6-7 million synthetic personas grounded in official Korean demographic statistics, designed to help build culturally accurate Korean AI agents while complying with Korea's Personal Information Protection Act (PIPA). The tutorial demonstrates how to filter personas and deploy a grounded Korean AI agent using hosted APIs in approximately 20 minutes.
KMMMU is a native Korean benchmark for evaluating multimodal understanding with 3,466 questions across nine disciplines and visual modality categories, addressing the gap of English-centric benchmarks by testing performance on Korean-specific cultural and institutional contexts.