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Paradot

by WithFeeling.AI

System Card

OrganizationWithFeeling.AI
Released2023-07
Architecturehierarchical-summary / Memory-to-Understanding Model (M2U)
DetailsParadot's proprietary Memory-to-Understanding Model is a matrix of LLMs ranging from several billion to tens of billions of parameters that captures a real-time evolving memory stream during conversations. Memories are categorized into levels based on their consolidation potential — from fleeting feelings to core facts — building a long-term evolving understanding of each user. Users can directly view, edit, delete, and favorite memories in a visible memory stream, making it the most user-transparent memory system among companion apps.
Parameters—
Domainpersonalizationepisodic-sessionlifelong-learning
Open SourceNo
WebsiteVisit
companionmemory-to-understandingemotional-aivisible-memoryuser-editableevolving

Capability Profile

Benchmark Scores

6 of 14 benchmarks
Data Transparency:6 estimated
Long-Context Retrieval
0/5
RULER
no data
NIAH
no data
LooGLE
no data
LongBench
no data
∞Bench
no data
Multi-Turn Recall
2/2
LoCoMo
76.463pEstimated
MemoryBank
76.958pEstimated
Cross-Session Memory
1/1
LongMemEval
74.743pEstimated
Multi-Hop QA
1/3
BABILong
76.863pEstimated
MultiHop-RAG
no data
HotpotQA
no data
Agent Task Memory
1/1
AgentBench-Mem
7226pEstimated
Personalization
1/1
PerLTQA
76.645pEstimated
Factuality / Grounding
0/1
RAGAS
no data
Sources:Arena estimate — derived from capability profile, not independently verified