Task-Oriented Dialogue Systems
Overview
Task-oriented dialogue systems help people complete goals—such as booking, getting support, or filling forms—by tracking what is known and deciding what to ask or do next. Common approaches include modular intent and slot filling with dialogue state tracking and policy selection, as well as end-to-end language models that use schemas, tools, databases, or structured controllers. Work is evaluated on benchmarks such as MultiWOZ, Schema-Guided Dialogue, and SIMMC, alongside spoken, multilingual, and real-world service settings; newer methods also use simulators and synthetic dialogues for training and testing. A central challenge is making systems reliable over long interactions: they must preserve constraints, handle missing or conflicting information, avoid hallucinations, and adapt to users whose behavior may differ from that of simulated users.
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