https://github.com/microsoft/WALNUT

A Benchmark on Semi-weakly Supervised Learning for Natural Language Understanding
https://github.com/microsoft/WALNUT

Last synced: 2 days ago
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A Benchmark on Semi-weakly Supervised Learning for Natural Language Understanding

• Host: GitHub
• URL: https://github.com/microsoft/WALNUT
• Owner: microsoft
• License: mit
• Created: 2022-05-04T20:05:08.000Z (over 2 years ago)
• Default Branch: main
• Last Pushed: 2023-07-26T04:42:07.000Z (over 1 year ago)
• Last Synced: 2025-01-23T00:06:06.643Z (10 days ago)
• Language: Python
• Size: 131 KB
• Stars: 4
• Watchers: 6
• Forks: 1
• Open Issues: 4
• Metadata Files:
  • Readme: README.md
  • License: LICENSE
  • Security: SECURITY.md

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• awesome-weak-supervision - codebase

README

        
# Code release for WALNUT

## Overview

This repository contains the baseline code for the WALNUT paper published in NAACL 2022. Detailed description about the data sets and methods can be manuscript at [here](https://arxiv.org/pdf/2108.12603.pdf).

## Getting data

Data for WALNUT can be downloaded from [here](https://github.com/gkaramanolakis/WALNUT_data).

## Repo structure

`document-level-baselines` contains source codes for 5 baseline mthods (C, W, Snorkel, C+W, C+Sonrkel) for document level classification tasks;

`document-level-GLC_MWNET_MLC` contains source codes for 3 advanced semi-weakly sueprvised learning methods (GLC, MetaWN, MLC) for document-level classification tasks;

`token-level-baselines` contains source codes for 5 baseline mthods (C, W, Snorkel, C+W, C+Sonrkel) for token-level classification tasks;

`token-level-GLC_MWNET_MLC` contains source codes for 3 advanced semi-weakly sueprvised learning methods (GLC, MetaWN, MLC) for token-level classification tasks.

## Citation

If you find WALNUT useful, please cite the following paper

```

@inproceedings{zheng2022walnut,

  title={WALNUT: A Benchmark on Semi-weakly Supervised Learning for Natural Language Understanding},

  author={Guoqing Zheng, Giannis Karamanolakis, Kai Shu, Ahmed Hassan Awadallah},

  booktitle={Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies},

  year={2022}

}

```

This code repository is released under MIT License. (See [LICENSE](LICENSE))