Measure Before You Manage: Evaluating Agent Working Memory in Coding Agents
[Sztuczna inteligencja] Autorzy: Le Chen, Zishen Wan, Baixi Sun i 6 więcej
Agent working memory is heterogeneous. Objects such as instructions, artifacts, tool outputs, and agent-generated state play different semantic roles and exhibit different size, retention, and representation profiles. Recent work has begun to explore memory-management mechanisms that account for such heterogeneity. This work focuses on semantic heterogeneity and studies how it should shape the management and evaluation of working memory in coding agents. Across 55 archived coding-agent trajectories, we find that semantically different working-memory objects exhibit distinct retention and compression behavior. This heterogeneity motivates semantically informed memory management. We study two semantically informed strategies: an object-aware compression policy and a retrieval-based policy. Their evaluation shows that calibration gains may not transfer to held-out tasks, and that equal tok…
- Kategoria arxiv
- cs.AI
- Kategoria
- Sztuczna inteligencja