SOURCE-LINKED INTELLIGENCE
PragAlign: Feedback-Guided Pragmatic Alignment for Controlled Synthetic Dialogue Generation
Synthetic dialogue generation can support research in privacy-restricted service settings, but generated conversations must preserve communicative intent, affective meaning, and natural dialogue flow. We introduce PragAlign, a feedback-guided framework for controlled synthetic dialogue generation conditioned on service context, target intent, and target emotion, with auxiliary trait-style controls. PragAlign uses a generate--evaluate--revise loop in which an LLM-based evaluator scores intent alignment, emotion alignment, coherence, fluency, and aggregate quality, then provides criterion-specif
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-02T11:49:55.000Z
First collected: 2026-09-21T05:32:15.665Z. This is not the publication date.