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This paper provides a mechanistic explanation for why LLMs lose track of instructions in long multi-turn interactions, introducing the Goal Accessibility Ratio (GAR) metric and a channel-transition framework. Through ablation studies and residual stream probes, it shows that attention to goal-defining tokens closes over turns while goal information persists in residual representations, with architecture-specific failure modes.