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arXiv · 2607.03974

TRACER: Early Failure Detection for Task-Oriented Dialogue

Erfan Nourbakhsh·Rocky Slavin·Ke Yang·Anthony Rios
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Abstract

Task-oriented dialogue systems often fail before the final breakdown is obvious, but most evaluation only measures failure after the conversation has already gone wrong. We present TRACER, a method for early failure detection in task-oriented dialogue. TRACER predicts from a partial dialogue whether the full conversation will eventually fail by combining simple trajectory signals from belief-state changes with text representations of the evolving dialogue state. We evaluate the method in both oracle and generated belief-state settings, and test how well it works when only 25%, 50%, 75%, or 100% of the dialogue is visible. Across these settings, TRACER detects useful failure signals well before the end of the conversation and outperforms heuristic, classical, and single-stream baselines. These results suggest that early failure detection can provide a practical warning signal for dialogue systems before the interaction fully breaks down.

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Erfan Nourbakhsh, Rocky Slavin, Ke Yang, Anthony Rios. 2026-07-04. TRACER: Early Failure Detection for Task-Oriented Dialogue. https://arxiv.org/abs/2607.03974

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