K-and-K/knights-and-knaves

Dataset

38

stars

17

commits

2

linked in READMEs

Oct 31, 2024

updated

logical
reasoning

README

πŸ“˜ knights-and-knaves Dataset [Project Page]

The knights-and-knaves dataset serves as a logical reasoning benchmark to evaluate the reasoning capabilities of LLMs.

πŸš€πŸš€ Check out the perturbed knights-and-knaves dataset to evaluate the memorization of LLMs in reasoning.

Loading the dataset

To load the dataset:

from datasets import load_dataset
data_subject = load_dataset('K-and-K/knights-and-knaves','test',split="2ppl")
  • Available subset: test, train.
  • Available split: 2ppl,3ppl,4ppl,5ppl,6ppl,7ppl,8ppl.

πŸ› οΈ Codebase

To evaluate LLMs on our datasets, visit our GitHub repository.

⭐ Citing our Work

If you find our codebase and datasets beneficial, kindly cite our work:

@article{xie2024memorization,
title={On Memorization of Large Language Models in Logical Reasoning}, 
author={Chulin Xie and Yangsibo Huang and Chiyuan Zhang and Da Yu and Xinyun Chen and Bill Yuchen Lin and Bo Li and Badih Ghazi and Ravi Kumar},
year={2024},
eprint={2410.23123},
archivePrefix={arXiv},
primaryClass={cs.CL},
url={https://arxiv.org/abs/2410.23123}, 
}

Contributors

alphapav

17 commits

K-and-K/knights-and-knaves

Dataset

38

stars

17

commits

2

linked in READMEs

Oct 31, 2024

updated

logical
reasoning

README

πŸ“˜ knights-and-knaves Dataset [Project Page]

The knights-and-knaves dataset serves as a logical reasoning benchmark to evaluate the reasoning capabilities of LLMs.

πŸš€πŸš€ Check out the perturbed knights-and-knaves dataset to evaluate the memorization of LLMs in reasoning.

Loading the dataset

To load the dataset:

from datasets import load_dataset
data_subject = load_dataset('K-and-K/knights-and-knaves','test',split="2ppl")
  • Available subset: test, train.
  • Available split: 2ppl,3ppl,4ppl,5ppl,6ppl,7ppl,8ppl.

πŸ› οΈ Codebase

To evaluate LLMs on our datasets, visit our GitHub repository.

⭐ Citing our Work

If you find our codebase and datasets beneficial, kindly cite our work:

@article{xie2024memorization,
title={On Memorization of Large Language Models in Logical Reasoning}, 
author={Chulin Xie and Yangsibo Huang and Chiyuan Zhang and Da Yu and Xinyun Chen and Bill Yuchen Lin and Bo Li and Badih Ghazi and Ravi Kumar},
year={2024},
eprint={2410.23123},
archivePrefix={arXiv},
primaryClass={cs.CL},
url={https://arxiv.org/abs/2410.23123}, 
}

Contributors

alphapav

17 commits