FlexStructRAG jointly constructs knowledge graphs, hypergraphs, and semantic clusters with dynamic partitioning to enable query-adaptive multi-granular retrieval that improves semantic scores over standard RAG baselines on UltraDomain.
Unifying large language models and knowledge graphs: A roadmap
2 Pith papers cite this work. Polarity classification is still indexing.
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A parallel encoding strategy with anchor-conditioned message passing and a merged relation graph allows entity alignment foundation models to generalize to unseen knowledge graphs by shortening the reasoning horizon.
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FlexStructRAG: Flexible Structure-Aware Multi-Granular Relational Retrieval for RAG
FlexStructRAG jointly constructs knowledge graphs, hypergraphs, and semantic clusters with dynamic partitioning to enable query-adaptive multi-granular retrieval that improves semantic scores over standard RAG baselines on UltraDomain.
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Breaking the Reasoning Horizon in Entity Alignment Foundation Models
A parallel encoding strategy with anchor-conditioned message passing and a merged relation graph allows entity alignment foundation models to generalize to unseen knowledge graphs by shortening the reasoning horizon.