When Errors Become Memories: Causal Pathway Tracing in Multi-Turn Memory-Augmented LLMs

Long-term memory allows large language models (LLMs) to preserve and reuse information across interaction turns, but it can also transform a localized error into a persistent system-level risk. Existing evaluations of memory-augmented LLMs focus primarily on whether information is correctly stored and retrieved, leaving the causal pathways through which errors persist and re-emerge insufficiently characterized. We introduce a structural causal framework for tracing cross-turn error propagation in memory-augmented LLMs. The framework models user questions, model responses, and memory states as a dynamic causal process, separates memory-update and question-feedback pathways, and uses four counterfactual trajectories to estimate their downstream effects and interaction. Error influence is evaluated through memory retention, natural responses, targeted diagnostic probes, and probability-level error preference. Across models, memory categories, injection positions, and memory mechanisms, error influence generally decreases with interaction distance but remains detectable in internal memory states and controlled behavior after disappearing from natural responses. The memory-update pathway produces more persistent effects on memory-state and probe outcomes, while question-feedback effects can be reactivated by later interactions. Pathway-guided restoration further supports this causal decomposition: repairing the corrupted memory state is more effective than repairing the affected question trajectory alone, and jointly restoring both pathways reduces residual propagation to 0.003, corresponding to a 98.5% reduction relative to the unrepaired condition. These findings show that response-only evaluation can miss latent error traces and that causal pathway tracing provides a principled basis for diagnosing and repairing persistent memory errors. Our code is available at https://anonymous.4open.science/r/Causal-Memory-Pathway-Tracing-33B0.