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A self-evolving agent rewrites its own harness and must decide which rewrites to keep, so its improvement signal is the check a rewrite has to pass. Verifying a rewrite by agent rollout is expensive and subjective, while executable checks such as the repository's own tests are too sparse to catch behavior-changing rewr...
This work proposes Trajectory Graph Copilot, a novel framework that acts as a ``copilot'' for LLM agents by diagnosing potential action errors before they are executed, significantly enhancing the agent's ability to complete long-horizon tasks successfully.
A novel framework, \textit{GAMER}~(Graph-based Action-centric Memory with Episodic Reasoning), that bridges the gap between inference scaling and episodic memory by decoupling the memory mechanism from LLMs.
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