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Multi-domain graph pre-training suffers from significant data redundancy; MDGMIX leverages boundary-aware subgraph mixing to achieve superior few-shot performance with improved efficiency.
Achieve 8x token reduction in million-token document understanding without sacrificing accuracy by having the LLM actively search for relevant information like a foraging animal.
