LLM-Driven Multi-Turn Task-Oriented Dialogue Synthesis for Realistic Reasoning

Researchers propose an LLM-driven framework for generating multi-turn task-oriented dialogues to create more realistic reasoning benchmarks. The framework addresses limitations in current AI evaluation methods by producing synthetic datasets that better reflect real-world complexity and contextual coherence.