AI Research
Profile-Graph Memory for LLM Agents: Implicit Cross-Entity Traversal through Narrative Profiles
Long-term memory is essential for LLM agents that interact across sessions, yet current memory benchmarks primarily evaluate single-hop recall, leaving multi-hop association largely unmeasured. We make three contributions. First, we introduce MemHop, a multi-hop memory benchmark ...
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ArXiv CS.AI
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ArXiv CS.AI
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This research introduces a novel memory system for LLM agents that excels at multi-hop reasoning by leveraging narrative profiles, significantly improving their ability to recall and connect information across extended interactions. The developed benchmark and architecture address a critical gap in evaluating and enhancing the long-term, context-aware capabilities of AI agents.
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