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--- |
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license: mit |
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task_categories: |
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- text-classification |
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language: |
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- en |
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tags: |
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- creative problem solving |
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- puzzles |
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- fixation effect |
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- large language models |
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- only connect |
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- quiz show |
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- connecting walls |
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pretty_name: Only Connect Wall Dataset |
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size_categories: |
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- n<1K |
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--- |
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<h1> |
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<img alt="Alt text" src="./rh-moustouche-hat.jpg" style="display:inline-block; vertical-align:middle" /> |
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Only Connect Wall (OCW) Dataset |
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</h1> |
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The Only Connect Wall (OCW) dataset contains 618 _"Connecting Walls"_ from the [Round 3: Connecting Wall](https://en.wikipedia.org/wiki/Only_Connect#Round_3:_Connecting_Wall) segment of the [Only Connect quiz show](https://en.wikipedia.org/wiki/Only_Connect), collected from 15 seasons' worth of episodes. Each wall contains the ground-truth __groups__ and __connections__ as well as recorded human performance. Please see [our paper](https://arxiv.org/abs/2306.11167) and [GitHub repo](https://github.com/TaatiTeam/OCW) for more details about the dataset and its motivations. |
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## Usage |
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```python |
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# pip install datasets |
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from datasets import load_dataset |
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dataset = load_dataset("TaatiTeam/OCW") |
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# The dataset can be used like any other HuggingFace dataset |
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# E.g. get the wall_id of the first example in the train set |
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dataset["train"]["wall_id"][0] |
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# or get the words of the first 10 examples in the test set |
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dataset["test"]["words"][0:10] |
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``` |
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We also provide two different versions of the dataset where the red herrings in each wall have been significantly reduced (`ocw_randomized`) or removed altogether (`ocw_wordnet`) which can be loaded like: |
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```python |
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# pip install datasets |
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from datasets import load_dataset |
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ocw_randomized = load_dataset("TaatiTeam/OCW", "ocw_randomized") |
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ocw_wordnet = load_dataset("TaatiTeam/OCW", "ocw_wordnet") |
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``` |
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See [our paper](https://arxiv.org/abs/2306.11167) for more details. |
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## 📝 Citing |
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If you use the Only Connect dataset in your work, please consider citing our paper: |
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``` |
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@article{alavi2024large, |
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title={Large Language Models are Fixated by Red Herrings: Exploring Creative Problem Solving and Einstellung Effect using the Only Connect Wall Dataset}, |
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author={Alavi Naeini, Saeid and Saqur, Raeid and Saeidi, Mozhgan and Giorgi, John and Taati, Babak}, |
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journal={Advances in Neural Information Processing Systems}, |
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volume={36}, |
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year={2024} |
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} |
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``` |
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## 🙏 Acknowledgements |
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We would like the thank the maintainers and contributors of the fan-made and run website [https://ocdb.cc/](https://ocdb.cc/) for providing the data for this dataset. We would also like to thank the creators of the Only Connect quiz show for producing such an entertaining and thought-provoking show. |