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MemoryLLM

by UCSD / Apple (Wang et al.)

System Card

OrganizationUCSD / Apple (Wang et al.)
Released2024-02
Architectureexternal-memory-network / Fixed-size latent memory pool updated in-place
DetailsLLM with an integrated fixed-size memory pool in latent space that self-updates as new text is injected. Parameters within the pool are continuously overwritten, enabling knowledge integration without retraining.
Parameters—
Domainlifelong-learninglong-context
Open SourceYes
PaperView Paper
CodeRepository
icml-2024self-updatablelatent-poolcontinual

Capability Profile

Benchmark Scores

6 of 14 benchmarks
Data Transparency:6 estimated
Long-Context Retrieval
3/5
RULER
no data
NIAH
no data
LooGLE
79.282pEstimated
LongBench
603pEstimated
∞Bench
8069pEstimated
Multi-Turn Recall
1/2
LoCoMo
76.363pEstimated
MemoryBank
no data
Cross-Session Memory
1/1
LongMemEval
75.248pEstimated
Multi-Hop QA
1/3
BABILong
82.194pEstimated
MultiHop-RAG
no data
HotpotQA
no data
Agent Task Memory
0/1
AgentBench-Mem
no data
Personalization
0/1
PerLTQA
no data
Factuality / Grounding
0/1
RAGAS
no data
Sources:Arena estimate — derived from capability profile, not independently verified