Spec-TOD: A Specialized Instruction-Tuned LLM Framework for Efficient Task-Oriented Dialogue Systems

Understand

Task-oriented dialogue (TOD) systems facilitate goal-driven interactions between users and machines.

• While recent advances in deep learning have improved the performance, TOD systems often struggle in low-resource scenarios with limited labeled data.
• To address this challenge, we propose Spec-TOD, a novel framework designed to train an end-to-end TOD system with limited data.
• Spec-TOD introduces two main innovations: (i) a novel specialized end-to-end TOD framework that incorporates explicit task instructions for instruction-tuned large language models (LLMs), and (ii) an efficient training strategy that leverages lightweight, specialized LLMs to achieve strong performance with minimal supervision.