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This paper introduces HiGram, an evolving hierarchical graph memory framework for LLM agents that features path-level localization and coordinated rewriting to improve retrieval efficiency and answer quality in long-term reasoning tasks.
MemDreamer decouples perception and reasoning for long video understanding using hierarchical graph memory and agentic retrieval, achieving state-of-the-art performance with reduced computational overhead.