# CommonGen

**Repository Path**: sina-wang/CommonGen

## Basic Information

- **Project Name**: CommonGen
- **Description**: 文本生成
- **Primary Language**: Python
- **License**: MIT
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2024-07-22
- **Last Updated**: 2024-07-22

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README


# Please check out the new repo: [https://github.com/allenai/CommonGen-Eval](https://github.com/allenai/CommonGen-Eval)

## CommonGen: A Constrained Text Generation Challenge Towards Generative Commonsense Reasoning


```
@article{lin2019comgen,
    author = {Bill Yuchen Lin  and Wangchunshu Zhou and Ming Shen and Pei Zhou and Chandra Bhagavatula and Yejin Choi and Xiang Ren},
    title = {CommonGen: A Constrained Text Generation Challenge for Generative Commonsense Reasoning},
    journal = {Findings of EMNLP},
    year = {2020}
}
```


**CommonGen** is a new _constrained text generation_ dataset that requires different kinds of commonsense to generate sentences about everyday scenarios, and thus targets **generative commonsense reasoning**. This repo is for tracking the latest dataset, some baseline models and our evaluation scripts. Please check [http://inklab.usc.edu/CommonGen/](http://inklab.usc.edu/CommonGen/) for more details. Note that our [arxiv article](https://arxiv.org/abs/1911.03705) may contain some _outdated_ statistics and information.


<img src="http://inklab.usc.edu/CommonGen/intro.png" width="700">

#### Content


- `methods` shows some baseline methods with many frameworks such as OpenNMT and Fariseq, as well as UniLM.

- `evaluation` contains the evaluation scripts for a variety of automatic metrics for testing the performance of system predictions against human-written results.

Please find our dataset at https://inklab.usc.edu/CommonGen/


#### Contact

Feel free to directly email yuchen[dot]lin[at]usc[dot]edu if you have any feedback.