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This paper introduces the Triple-Stream Stress (TSS) diagnostic framework to uncover lexical interference and label bias in mental health NLP, proposing the Degree of Divergence metric for label-source auditing.
This paper reframes empathy in AI dialogue systems as 'predictive misalignment tolerance' and proposes an Interpretive Error Tolerance (IET) heuristic. Experiments reveal that dialogue repair has a regime-dependent structure, trading off discriminative fidelity for gist preservation under different noise levels.