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Long-term emotional-support agents require memory mechanisms for personalized understanding across sessions. However, emotional-support dialogue is often low-density: turns are incomplete, evidence is scattered, and user states evolve over time. Existing memory methods usually rely on fixed units, such as turn-level no...
The results support frozen verification as a training signal for evidence selection, while showing that strict boundary precision remains comparatively weaker.
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