RESEARCH27
Knowledge-driven Augmentation and Retrieval for Integrative Temporal Adaptation
arXiv CS.CLΒ·April 27, 2026
KARITA (Knowledge-driven Augmentation and Retrieval for Integrative Temporal Adaptation) is a system developed to address the challenges of temporal shifts in AI models, which are trained on historical data but deployed on future data. It integrates knowledge-driven augmentation and retrieval to capture diverse shifts and leverage insights for improved temporal adaptation across multiple domains.
temporal adaptationmodel adaptationmachine learningKnowledge Representationretrieval augmented learning
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