Influenciæ: A Library for Tracing the Influence Back to the Data-Points

EXPLAINABLE ARTIFICIAL INTELLIGENCE, XAI 2024, PT IV(2024)

引用 0|浏览0
摘要
In today's AI-driven world, understanding model behavior is becoming more important than ever. While libraries abound for doing so via traditional XAI methods, the domain of influence-based techniques for data-centric explanations remains mostly underserved. To fill this void, we introduce Influenciae (Available at: https://github.com/deel-ai/influenciae), an open-source library that implements the state-of-the-art methods for estimating the influence of training points on the model, with a focus on efficiency and scalability to fit the needs and the recent trends in the field. Finally, we have thoroughly documented and included plenty of tutorials to make the library reachable to the public, in the hopes that it will bring these methods back into the spotlight.
更多
查看译文
关键词
Data-centric,XAI,Influence functions,Open-source library
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
0
您的评分 :

暂无评分

数据免责声明
页面数据均来自互联网公开来源、合作出版商和通过AI技术自动分析结果,我们不对页面数据的有效性、准确性、正确性、可靠性、完整性和及时性做出任何承诺和保证。若有疑问,可以通过电子邮件方式联系我们:report@aminer.cn