Experiments on two domains of the MultiDoGO dataset reveal challenges of constraint violation detection and sets the stage for future work and enhancements. The results from the empirical work present that the new rating mechanism proposed shall be simpler than the previous one in a number of facets. Extensive experiments and analyses on the lightweight fashions present that our proposed strategies obtain significantly greater scores and considerably enhance the robustness of each intent detection and slot filling. Data-Efficient Paraphrase Generation to Bootstrap Intent Classification and Slot Labeling for new Features in Task-Oriented Dialog Systems Shailza Jolly author ยิงปลาฟรี Tobias Falke creator Caglar Tirkaz creator Daniil Sorokin author 2020-dec textual content Proceedings of the 28th International Conference on Computational Linguistics: Industry Track International Committee on Computational Linguistics Online convention publication Recent progress via advanced neural models pushed the performance of task-oriented dialog methods to nearly excellent accuracy on current benchmark datasets for intent classification and slot labeling.