자연어처리 및 시각 분야 발전에 따라 인간의 인지 능력과 사고 방식을 모방하기 위하여 구성성(compositionality) 연구 또한 활발히 진행 중이다. 구성성은 표현의 의미가 부분 요소들의 의미와 결합 규칙에 따라 결정된다는 원리로, 인간의 인지적 사고방식을 모사하는 데 중요한 개념이다. 최근 연구는 주로 구성적 일반화(compositional generalization) 능력을 평가하는 데이터셋을 중심으로 이루어지고 있으며, 대표적으로 자연어처리 분야에서는 COGS, CFQ, PCFG, SCAN, gSCAN이, 시각 분야에서는 CREPE가 사용된다. 이 데이터셋은 구성성의 다섯 가지 핵심 요소인 체계성(Systematicity), 생산성(Productivity), 대체성(Substitutivity), 지역주의(Localism), 과잉 일반화(Overgeneralization)를 기반으로 구성성 평가를 수행한다. 본 논문은 이 데이터셋들을 사용한 연구 결과를 종합하여 구성적 일반화의 중요성과 모델들의 한계를 분석하고 향후 연구 방향을 제시한다.
Keyword
구성성, 구성적 일반화, 자연어처리 구성성, 비전 구성성
KSP Keywords
Natural Language processing
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