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- creativity: 창의성 및 계산 창의성 연구 (11개) - economy: 경제 원리 및 토큰 이코노미 (11개) - explainability: 설명 가능한 AI (XAI) 연구 (11개) - gamification: 게이미피케이션 이론 (11개) - sociology_of_agents: 에이전트 사회학 (11개) - README.md 업데이트
666 B
666 B
Interpretability Beyond Feature Attribution: Quantitative Testing with Concept Activation Vectors (TCAV)
- Authors: Been Kim, Martin Wattenberg, Justin Gilmer, Carrie Cai, James Wexler, Fernanda Viegas, Rory Sayres
- Year: 2018
- Summary: TCAV moves beyond explaining predictions in terms of low-level features and instead explains them in terms of high-level, human-understandable concepts. It quantifies the degree to which a user-defined concept (e.g., 'stripes' for a zebra classifier) is important to a model's prediction for a class of inputs. This allows for more global and intuitive explanations.
- Link: https://arxiv.org/abs/1711.11279