ReacTOD: Bounded Neuro-Symbolic Agentic NLU for Zero-Shot Dialogue State Tracking

ReacTOD introduces a bounded neuro-symbolic architecture for task-oriented dialogue systems, reformulating NLU as discrete tool calls within a self-correcting ReAct loop. It improves accuracy by up to 9.3 percentage points and achieves a 93.1% self-correction rate on intercepted errors.