ConMem: Structured Memory-Guided Adaptation in Training-Free Multi-Agent Systems

Published
Source
arXiv
Paper number
376
Field
AI / General
arXiv ID
2606.08702

Key points

  • It distills past trajectories into typed signed memory cards to create reusable strategic units.
  • It organizes the cards as typed graphs with supports, satisfies, conflicts, and constrains relations.
  • It uses needs-aware retrieval to search for cards that match the current task.
  • It resolves conflicts and recovers dependencies through the relation graph to produce consistent guidance.
  • Context-budget control prunes more than 50% of candidate cards and reduces planning overhead by 80%.
  • It is training-free and does not require changes to the host model weights or orchestration.

Paper links

External research summaries. These are not HDATF publications or measured product results.

Read original (opens in a new tab)