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GRALAN enables KGs to speak directly in the LLM's semantic space through relational tokens that preserve graph structure. No fine-tuning required — just trainable language mediation.
X-KGRank unifies structural collaborative filtering with LLM-based explanation. A 1.5B parameter model matches a 7B model on explanation quality — but fabricates facts more often when not grounded.
Human developers build partial dependency graphs on-demand — not static global graphs. DyRetriever replicates this pattern, achieving +59.73% Pass@1 on DevEval while being 7.4x faster.
Persona-memory systems suffer from a validity gap — personas drift without traceable evidence. PGMem solves this with a heterogeneous graph that keeps every signal traceable to its source events.
Zero-knowledge proofs moved from silicon to chemistry. Graph isomorphism proofs encoded in synthetic DNA — hardware-independent, quantum-resistant, potentially uncloneable cryptography.
Agents should navigate document structure rather than repeatedly search from scratch. DocNavRAG maintains an evolving evidence state that improves answer quality by 7.8% and context sufficiency by 17.7%.