AnthroDial Framework Creates More Human-Like AI Chat

Creating AI chat systems that genuinely mimic human private conversation requires more than just fluent responses; they must maintain persona, relationship context, memory, bounded knowledge, and appropriate timing across multi-turn interactions. The AnthroDial framework addresses this by integrating system architecture, executable evaluation, and diagnostic alignment into a unified closed-loop approach. AnthroDial features a sophisticated role-conditioned scheduled dialogue runtime that incorporates persona and scenario cards, long-term memory, virtual time, and single-draft message decisions. This architecture allows for nuanced, context-aware interactions. The framework also includes an executable benchmark with a validity gate and ten distinct per-turn and dialogue-level evaluation dimensions. A post-training pipeline uses SFT and GRPO with a cognitive-diagnostic, ZPD-aware reward mechanism. This reward system dynamically adjusts based on estimated capability deficits and focuses optimization on learnable weak skills, significantly improving anthropomorphic dialogue performance over baseline models.