Ekova: A Personality-Support Agent for Self-Discovery Dialogue

Abstract:Emotional Support (ES) systems have long optimized a single objective: alleviating the user's emotional distress in the moment. We argue that a complementary need, helping users see themselves more clearly, defines a distinct paradigm we call Personality Support (PS). PS is not counseling or clinical intervention: it targets cognitive clarity and self-articulation, not symptom relief or diagnosis. We instantiate this paradigm in three layers. First, we present DSD, a Chinese self-discovery PS Dataset of 8,590 samples collected through real longitudinal interaction across five minimal units, Coach, Warm, Tsukkomi, Real, and Gonzo. Second, we build DeepSupport, a multi-persona PS system trained with OrthoTune, a PS-tailored framework with style-specific adapters and a style-consistency regularizer. Third, we unify the five DeepSupport personas into Ekova, a persistent personality-support agent with a unified cross-session memory layer, supporting both adaptive routing and user-customized persona selection. Experiments show that OrthoTune-trained models outperform all baselines with an average relative gain of 16.3% across all metrics over the strongest prompt-based baseline. Code is available at this https URL.

Artificial Intelligence (cs.AI); Human-Computer Interaction (cs.HC)

arXiv:2608.00478 [cs.AI]

(or arXiv:2608.00478v1 [cs.AI] for this version)

https://doi.org/10.48550/arXiv.2608.00478 Focus to learn more arXiv-issued DOI via DataCite (pending registration)

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