Knowledge Tree
Relations (1)
related 2.32 — strongly supporting 4 facts
Machine learning and explanation are linked as core research areas within the KR 2026 special track, which explores their synergistic interactions with Knowledge Representation [1]. Both fields are identified as key components for hybrid solutions and evaluation protocols [2], and they serve as primary domains for the application of Knowledge Representation technologies [3].
Facts (4)
Sources
Call for Papers: KR meets Machine Learning and Explanation kr.org 4 facts
perspectiveThe field of Knowledge Representation (KR) provides a repertoire of technologies for leveraging knowledge in both Machine Learning (ML) and explanation pipelines.
procedureThe KR 2026 special track 'KR meets Machine Learning and Explanation' mandates that all submissions must fall into the intersection of Knowledge Representation and either Machine Learning or explanation; papers that do not meet this criterion will be desk-rejected before the review process begins.
claimThe KR 2026 special track on 'KR meets Machine Learning and Explanation' aims to focus on the synergistic interactions between Knowledge Representation (KR) and the fields of Machine Learning (ML) and explanation.
claimThe KR 2026 special track welcomes papers focusing on evaluation protocols and benchmarking of hybrid solutions that combine Knowledge Representation (KR) with Machine Learning (ML) or explanation.