Datasets:

wenhu
/

TheoremQA

Tasks:

Question Answering

Languages: English

Size Categories: n<1K

ArXiv:

Tags: question answering math science visual question answering

License:

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Cannot get the config names for the dataset.

Error code:   ConfigNamesError
Exception:    ValueError
Message:      Couldn't infer the same data file format for all splits. Got {'train': (None, {}), 'test': ('parquet', {})}
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/dataset/config_names.py", line 66, in compute_config_names_response
                  config_names = get_dataset_config_names(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/inspect.py", line 347, in get_dataset_config_names
                  dataset_module = dataset_module_factory(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1879, in dataset_module_factory
                  raise e1 from None
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1854, in dataset_module_factory
                  return HubDatasetModuleFactoryWithoutScript(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1245, in get_module
                  module_name, default_builder_kwargs = infer_module_for_data_files(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 593, in infer_module_for_data_files
                  raise ValueError(f"Couldn't infer the same data file format for all splits. Got {split_modules}")
              ValueError: Couldn't infer the same data file format for all splits. Got {'train': (None, {}), 'test': ('parquet', {})}

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Introduction

We propose the first question-answering dataset driven by STEM theorems. We annotated 800 QA pairs covering 350+ theorems spanning across Math, EE&CS, Physics and Finance. The dataset is collected by human experts with very high quality. We provide the dataset as a new benchmark to test the limit of large language models to apply theorems to solve challenging university-level questions. We provide a pipeline in the following to prompt LLMs and evaluate their outputs with WolframAlpha.

How to use TheoremQA

from datasets import load_dataset

dataset = load_dataset("wenhu/TheoremQA")

for d in dataset['test']:
  print(d)

Arxiv Paper:

https://arxiv.org/abs/2305.12524

Code

https://github.com/wenhuchen/TheoremQA/tree/main

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