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G2PO redefines agent actions and leverages a global state-transition graph, leading to a 22.2% boost in success rates for long-horizon tasks.
LLMs can now leverage a hierarchical graph structure for memory retrieval, enabling global reasoning and boosting performance on long-term memory benchmarks beyond what's achievable with similarity search alone.
