Efficient Tool-Calling Multi-Expert NPC Agent for Commonsense Persona-Grounded Dialogue

Nuriyev, Mahammad

arXiv.org Artificial Intelligence 

We present a multi-expert system for creating Non-Player Characters (NPCs) capable of both natural dialogue and contextual action execution in interactive environments. Our approach leverages Qwen3 as the base model with specialized Low-Rank Adaptation (LoRA) adapters to create three distinct expert modules: tool calling, tool response interpretation, and direct dialogue. The system not only meets but exceeds the computational constraints, delivering responses in an average of 3 seconds (well under the 7-second limit) on L40S GPUs while utilizing less than 30GB of the available 48GB VRAM, demonstrating efficiency alongside performance. This computational efficiency also contributes to reduced energy consumption and lower carbon footprint compared to less optimized approaches. The proposed solution achieved top performance in the Commonsense Persona-Grounded Dialogue Challenge 2025, securing the second position in the competition.

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