AI & Machine Learning

I built an Agent Memory System for myself and got 90.8% (end-to-end) on LongMemEval

Ali Nemati14 hours ago27 sec read4 views0 listens

A developer created Memento, a bitemporal knowledge graph memory system for AI agents, which achieved 90.8% accuracy on the LongMemEval benchmark. This system outperforms traditional vector stores by resolving entities and tracking temporal changes, enhancing its ability to answer complex queries accurately. The project highlights the importance of quality over quantity in retrieval methods and warns against multi-pass generation techniques that can corrupt correct answers.

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