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
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Paper → model → repo connections mined from source citations (Tier-1 exact match).
Why these links exist
- Linked via arxiv authorShengguang Wu →
AutoMem: Automated Learning of Memory as a Cognitive Skill
- Linked via arxiv authorHao Zhu →
AutoMem: Automated Learning of Memory as a Cognitive Skill
- Linked via arxiv authorYuhui Zhang →
AutoMem: Automated Learning of Memory as a Cognitive Skill
- Linked via arxiv authorXiaohan Wang →
AutoMem: Automated Learning of Memory as a Cognitive Skill
- Linked via arxiv authorSerena Yeung-Levy →
AutoMem: Automated Learning of Memory as a Cognitive Skill
