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

WALNUT: A Benchmark on Semi-weakly Supervised Learning for Natural Language Understanding

WALNUT is a benchmark for semi-weakly supervised learning for natural language understanding. It consists of 8 NLU tasks with different types, including document-level and token-level prediction tasks.

Data and Resources

This dataset has no data

Cite this as

Guoqing Zheng, Giannis Karamanolakis, Kai Shu, Ahmed Hassan Awadallah (2024). Dataset: WALNUT: A Benchmark on Semi-weakly Supervised Learning for Natural Language Understanding. https://doi.org/10.57702/38cjkr9b

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.2108.12603
Author	Guoqing Zheng
More Authors	Giannis Karamanolakis Kai Shu Ahmed Hassan Awadallah
Homepage	https://aka.ms/walnut_benchmark