Closing the Consistency Gap: Self-Evolving Agents That Learn to Stay on Course
This work presents a self-evolving agent framework that reduces the consistency gap by identifying unstable, low-consistency steps in agent trajectories and converting them into episodic memory the agent can draw on in future runs.