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TrajDebug uncovers the root causes of failures in long-horizon agent trajectories, enabling targeted improvements that could significantly boost agent performance.
LLMs exhibit a troubling tendency to prioritize code generation over genuine architectural understanding, revealing a critical gap in their evaluation metrics.
