AutoMem: Automated Learning of Memory as a Cognitive Skill
Memory expertise is a learned skill: knowing what to encode, when to retrieve, and how to organize knowledge--a capacity known in cognitive science as metamemory. We bring this perspective to LLMs by treating memory management as a trainable skill. We promote file-system operations to first-class memory actions alongside task actions, letting the model itself decide how to manage its memory. This memory skill improves along two axes: the structure that supports it (prompts, file schemas, action vocabulary), and the proficiency of the model exercising it. Both axes resist manual optimization: e
Lineage graph
Paper → model → repo connections mined from source citations (Tier-1 exact match).
Why these links exist
Every edge carries a method, confidence, and the source snippet that justified it — so bad links are debuggable.
- LinkedLinked via unknownIEEE Rolls Out Large Language Models Virtual Training Course →
- LinkedLinked via arxiv author · 85%Shengguang Wu →
“AutoMem: Automated Learning of Memory as a Cognitive Skill”
- LinkedLinked via arxiv author · 85%Hao Zhu →
“AutoMem: Automated Learning of Memory as a Cognitive Skill”
- LinkedLinked via arxiv author · 85%Yuhui Zhang →
“AutoMem: Automated Learning of Memory as a Cognitive Skill”
- LinkedLinked via arxiv author · 85%Xiaohan Wang →
“AutoMem: Automated Learning of Memory as a Cognitive Skill”
- LinkedLinked via arxiv author · 85%Serena Yeung-Levy →
“AutoMem: Automated Learning of Memory as a Cognitive Skill”
- PossiblePossibly related (embedding) · 46%GuyMannDude/mnemo-cortex →