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The MultiWOZ dataset (Budzianowski et al.,2018) is frequently used forbenchmarking context-to-response abilities of task-oriented dialogue systems.In this work, we identify inconsistencies in data preprocessing and reportingof three corpus-based metrics used on this dataset, i.e., BLEU score and Inform& Success rates. We point out a few problems of the MultiWOZ benchmark such asunsatisfactory preprocessing, insufficient or under-specified evaluationmetrics, or rigid database. We re-evaluate 7 end-to-end and 6 policyoptimization models in as-fair-as-possible setups, and we show that theirreported scores cannot be directly compared. To facilitate comparison of futuresystems, we release our stand-alone standardized evaluation scripts. We alsogive basic recommendations for corpus-based benchmarking in future works.

Shades of BLEU, Flavours of Success: The Case of MultiWOZ