pith:W6LXFWZS
MemORAI: Memory Organization and Retrieval via Adaptive Graph Intelligence for LLM Conversational Agents
MemORAI equips LLMs with selective memory filtering, provenance tracking, and adaptive retrieval to enable coherent long-term personalized conversations.
arxiv:2605.01386 v2 · 2026-05-02 · cs.CL
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Claims
Evaluated on LOCOMO and LongMemEval benchmarks, MemORAI achieves state-of-the-art performance in memory retrieval and personalized response generation, demonstrating that selective storage, enriched representation, and adaptive retrieval are essential for coherent, personalized LLM agents.
The assumption that the three proposed components (dual-layer compression with selective filtering, turn-level provenance in the multi-relational graph, and query-conditioned edge weighting in Dynamic Weighted PageRank) will reliably solve information dilution and uniform retrieval problems without introducing new overhead or retrieval biases that could degrade performance on unseen conversation styles or domains.
MemORAI combines selective filtering, provenance tracking in multi-relational graphs, and dynamic weighted PageRank retrieval to achieve state-of-the-art memory retrieval and personalized responses in LLM agents on LOCOMO and LongMemEval benchmarks.
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| First computed | 2026-06-03T01:05:14.332464Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
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curl -sH 'Accept: application/ld+json' https://pith.science/pith/W6LXFWZSBPEO3LDGK5XPVYJ4X7 \
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Canonical record JSON
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