본 논문은 온디바이스 사이버범죄 데이터 전처리 지원을 위해 Llama-3.2-3B-Instruct 의 경량화 기법별 성능 저하
패턴을 분석한다. 가지치기와 양자화 기법을 적용하여 재학습 유무 및 희소성 수준에 따른 지시 이행 능력을 IFEval 과
GPT-5.1 기반으로 검증하였다. 실험 결과 재학습을 병행한 경량화가 단순 기법 대비 유의미한 성능 방어 효과를
보였으며, 이는 자원 제한적 환경에서의 효율적인 모델 최적화 전략 수립에 기여할 것으로 기대된다.
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