ClairTrelo - 17-11-2023 at 03:12 AM
Experiments on two domains of the MultiDoGO dataset reveal challenges of constraint violation detection and sets the stage for future work and
improvements. The outcomes from the empirical work present that the new ranking mechanism proposed can be more effective than the previous one in a
number of points. Extensive experiments and analyses on the lightweight models present that our proposed strategies achieve considerably greater
scores and substantially improve the robustness of both 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 Tobias Falke creator Caglar Tirkaz author
Daniil Sorokin creator 2020-dec text Proceedings of the 28th International Conference on Computational Linguistics: Industry Track International
Committee on Computational Linguistics Online conference publication Recent progress through advanced neural models pushed the efficiency of
process-oriented dialog programs to almost good accuracy on present benchmark datasets for intent classification and slot labeling.