A unified taxonomy of agent context compression along three dimensions is introduced: compression target (what is compressed), compression mechanism (how it is transformed and retained), and control policy (who decides when compression is triggered).
It is found that fewer tokens need not mean faster or cheaper execution: on Terminal-Bench with Qwen, policies using roughly one-third as many tokens can take 20-80% longer than the uncompressed agent.
Ritul Satish, Prasoon Sinha, Akiho Kawada et al.· 0 citations
Behavioral topology is shaped more by the deployment harness than by the LLM, providing a model-agnostic structural primitive for safety auditing and runtime monitoring, and addresses both prediction goals.
Seonglae Cho, F. Fernandez, Umar Mohammed et al.· 3 citations
This paper proposes FRESH, a Failure-aware Retrieval framework over Experience-Structured Heterogeneous graphs, which transforms historical successes and failures into structured external experience for tool-using agents and consistently improves task success and tool-use reliability over no-memory agents and represent...
Jia-Xing Li, Lei Song, Rui Dong et al.· 0 citations
Dynamic Retrieval-based Policy Generation (DRPG) is proposed, a framework that integrates memory-based retrieval with a dynamic policy generator, leveraging historical data and environment feedback to produce task-specific policies for continual LLM improvement.
Ting-Wei Chang, Po-Chun Chen, Hen-Hsen Huang et al.· 0 citations
It is argued that context assembly in ContextPipe is structurally isomorphic to query execution in a relational database: both execute under a hard budget, exploit a tiered cache, and leverage statistics.
Peng Xu, Zu-Yu Zhang, Yu-Ze Sun et al.· 0 citations
A controlled runtime measurement protocol for reacquisition cost in a bounded-horizon tool-using agent and three models across two task regimes are evaluated, showing that the reacquisition signature is environment-dependent rather than intrinsic to shortening context.
Shuyu Liu· 0 citations
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