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

TL;DR

This paper introduces an efficient multi-expert NPC system that combines tool calling, response interpretation, and dialogue generation, achieving high performance and resource efficiency in persona-grounded dialogue tasks.

Contribution

The paper presents a novel multi-expert architecture using Qwen3 and LoRA adapters for efficient NPC dialogue and action, with competitive ranking in a major challenge.

Findings

Achieved second place in the Commonsense Persona-Grounded Dialogue Challenge 2025.

Maintains fast response times with modest GPU resources.

Demonstrates effective integration of tool calling and dialogue in NPCs.

Abstract

We present a multi-expert system for creating Non-Player Characters (NPCs) capable of both natural dialogue and contextual action execution in interactive environments. Using Qwen3 as the base model and Low-Rank Adaptation (LoRA) adapters, we instantiate three specialists: tool calling, tool-response interpretation, and direct dialogue. Our system comfortably meets the computational efficiency requirements, delivering fast responses and maintaining modest resource usage on L40S GPUs. In the Commonsense Persona-Grounded Dialogue Challenge 2025, our method ranked second overall. Code available at: https://github.com/MahammadNuriyev62/CPDC-challenge-2025-solution/