Definition
Memora is a harmonic memory representation framework for long-horizon AI agents, published at ICML 2026 by microsoft Research. It decouples rich memory content from lightweight retrieval abstractions and cue anchors.
Key Points
- Primary abstractions: Short phrases (6–8 words) index memory values; only abstractions are embedded for similarity search
- Cue anchors: Context-aware tags providing alternative retrieval paths and cross-memory links
- Retrieval policy: Markov Decision Process navigation beyond direct semantic similarity
- Benchmarks: SOTA LoCoMo 86.3%, LongMemEval 87.4%; up to 98% fewer context tokens vs full-history baseline
- Theory: Standard rag and knowledge-graph memory emerge as special cases
- Open source: Code on GitHub; paper arXiv:2602.03315