RAD automatically extracts weighted, hierarchical decision criteria from documents and uses LLMs to generate structured decision reports, but its evaluation is largely self-referential.
A framework for developing a knowledge management platform
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abstract
Knowledge management (KM) involves collecting, organizing, storing, and disseminating information to improve decision-making, innovation, and performance. Implementing KM at scale has become essential for organizations to effectively leverage vast accessible data. This paper is a compilation of concepts that emerged from KM workshops hosted by EMBL-EBI, attended by SMEs and industry. We provide guidance on envisioning, executing, evaluating, and evolving knowledge management platforms. We emphasize essential considerations such as setting knowledge domain boundaries and measuring success, as well as the importance of making knowledge accessible for downstream applications and non-computational users and highlights necessary personal and organizational skills for success. We stress the importance of collaboration and the need for convergence on shared principles and commitment to provide or seek resources to advance KM. The community is invited to join the journey of KM and contribute to the advancement of the field by applying and improving on the guidelines described.
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cs.AI 1years
2025 1verdicts
REJECT 1roles
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unclear 1representative citing papers
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Retrieval Augmented Decision-Making: A Requirements-Driven, Multi-Criteria Framework for Structured Decision Support
RAD automatically extracts weighted, hierarchical decision criteria from documents and uses LLMs to generate structured decision reports, but its evaluation is largely self-referential.