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LangChain launches OpenWiki Brains, a framework for proactive memory for AI agents that automatically builds and updates wikis from connected sources like Gmail, Notion, and git repos.
This paper introduces a proactive memory agent that operates alongside a standard action agent to selectively inject memory-grounded reminders during long-horizon tasks, mitigating behavioral state decay. Experiments on Terminal-Bench and τ²-Bench show significant improvements in pass@1, and the approach is demonstrated with both weak and strong action agents.
Meta researchers propose a proactive memory agent that runs alongside an unmodified action agent to surface relevant past decisions and prevent forgetting in long-horizon tasks. Their method improves pass@1 on Terminal-Bench 2.0 and tau-squared-Bench by 8.3 and 6.8 percentage points respectively.
This paper introduces a proactive memory agent that runs alongside an action agent to prevent behavioral state decay in long-horizon tasks, achieving significant improvements on Terminal-Bench2.0 and τ^2-Bench. The authors also train Qwen3.5-27B using SFT and GRPO as an early step toward open-weight memory policies.
Introduces Cognifold, a brain-inspired always-on proactive memory for LLM agents that continuously organizes fragmented event streams into self-emerging cognitive structures via graph-topology self-organization, extending Complementary Learning Systems theory with a prefrontal intent layer.