You're currently viewing an old version of this dataset. To see the current version, click here.

SNOiC: Soft Labeling and Noisy Mixup based Open Intent Classification Model

This paper presents a Soft Labeling and Noisy Mixup-based open intent classification model (SNOiC). Most of the previous works have used threshold-based methods to identify open intents, which are prone to overfitting and may produce biased predictions.

Data and Resources

This dataset has no data

Cite this as

Aditi Kanwar, Aditi Seetha, Satyendra Singh Chouhan, Rajdeep Niyogi (2024). Dataset: SNOiC: Soft Labeling and Noisy Mixup based Open Intent Classification Model. https://doi.org/10.57702/wry4xovf

Private DOI This DOI is not yet resolvable.
It is available for use in manuscripts, and will be published when the Dataset is made public.

Additional Info

Field	Value
Created	December 16, 2024
Last update	December 16, 2024
Defined In	https://doi.org/10.48550/arXiv.2310.07306
Author	Aditi Kanwar
More Authors	Aditi Seetha Satyendra Singh Chouhan Rajdeep Niyogi