https://github.com/ofirpress/self-ask

Code and data for "Measuring and Narrowing the Compositionality Gap in Language Models"
https://github.com/ofirpress/self-ask

Last synced: 3 months ago
JSON representation

Code and data for "Measuring and Narrowing the Compositionality Gap in Language Models"

• Host: GitHub
• URL: https://github.com/ofirpress/self-ask
• Owner: ofirpress
• License: mit
• Created: 2022-10-04T07:29:59.000Z (about 2 years ago)
• Default Branch: main
• Last Pushed: 2023-12-28T21:00:09.000Z (11 months ago)
• Last Synced: 2024-06-15T12:32:16.434Z (5 months ago)
• Language: Jupyter Notebook
• Size: 646 KB
• Stars: 286
• Watchers: 6
• Forks: 31
• Open Issues: 1
• Metadata Files:
  • Readme: README.md
  • License: license.txt

Awesome Lists containing this project

• awesome-ChatGPT-repositories - self-ask - Code and data for "Measuring and Narrowing the Compositionality Gap in Language Models" (NLP)

README

        
# self-ask

This repo contains the code and data for our ["Measuring and Narrowing the Compositionality Gap in Language Models" paper](https://arxiv.org/abs/2210.03350), presented at Findings of EMNLP 2023. 

You can read more about self-ask prompting [here (including a 2 minute demo video)](https://ofir.io/Self-ask-prompting/). 

Or read more about our Compositional Celebrities dataset, and the Compositionality Gap [here (also includes a 2 minute video)](https://ofir.io/The-compositionality-gap-and-compositional-celebrities/). 

Lastly, you can learn more about our Bamboogle dataset [here (includes a 2 minute video)](https://ofir.io/The-Bamboogle-Dataset/).

### Citation:

```

@inproceedings{press-etal-2023-measuring,

    title = "Measuring and Narrowing the Compositionality Gap in Language Models",

    author = "Press, Ofir  and

      Zhang, Muru  and

      Min, Sewon  and

      Schmidt, Ludwig  and

      Smith, Noah  and

      Lewis, Mike",

    editor = "Bouamor, Houda  and

      Pino, Juan  and

      Bali, Kalika",

    booktitle = "Findings of the Association for Computational Linguistics: EMNLP 2023",

    month = dec,

    year = "2023",

    address = "Singapore",

    publisher = "Association for Computational Linguistics",

    url = "https://aclanthology.org/2023.findings-emnlp.378",

    doi = "10.18653/v1/2023.findings-emnlp.378",

    pages = "5687--5711",

}

```