The dataset viewer is not available for this dataset.
Cannot get the config names for the dataset.
Error code:   ConfigNamesError
Exception:    TypeError
Message:      'str' object is not a mapping
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 164, in get_dataset_config_names
                  dataset_module = dataset_module_factory(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1729, in dataset_module_factory
                  raise e1 from None
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1686, in dataset_module_factory
                  return HubDatasetModuleFactoryWithoutScript(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1038, in get_module
                  dataset_infos = DatasetInfosDict.from_dataset_card_data(dataset_card_data)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/info.py", line 386, in from_dataset_card_data
                  dataset_info = DatasetInfo._from_yaml_dict(dataset_card_data["dataset_info"])
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/info.py", line 317, in _from_yaml_dict
                  yaml_data["features"] = Features._from_yaml_list(yaml_data["features"])
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/features/features.py", line 1979, in _from_yaml_list
                  return cls.from_dict(from_yaml_inner(yaml_data))
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/features/features.py", line 1975, in from_yaml_inner
                  return {name: from_yaml_inner(_feature) for name, _feature in zip(names, obj)}
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/features/features.py", line 1975, in <dictcomp>
                  return {name: from_yaml_inner(_feature) for name, _feature in zip(names, obj)}
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/features/features.py", line 1972, in from_yaml_inner
                  return {"_type": snakecase_to_camelcase(_type), **unsimplify(obj)[_type]}
              TypeError: 'str' object is not a mapping

Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.

Overview

This dataset contains leaderboard conversation data collected between June 2024 and August 2024.

It includes English human preference evaluations used to develop Arena Explorer. Additionally, we provide an embedding file, which contains precomputed embeddings for the English conversations. These embeddings are used in the topic modeling pipeline to categorize and analyze these conversations.

For a detailed exploration of the dataset and analysis methods, refer to the notebook and blogpost, which provides a step-by-step workflow for processing data and insights derived.

License

User prompts are licensed under CC-BY-4.0, and model outputs are governed by the terms of use set by the respective model providers.

Citation

@misc{tang2025explorer,
    title={Arena Explorer: A Topic Modeling Pipeline for LLM Evals & Analytics},
    author={Kelly Tang and Wei-Lin Chiang and Anastasios N. Angelopoulos}
    year={2025},
}

@misc{chiang2024chatbot,
    title={Chatbot Arena: An Open Platform for Evaluating LLMs by Human Preference},
    author={Wei-Lin Chiang and Lianmin Zheng and Ying Sheng and Anastasios Nikolas Angelopoulos and Tianle Li and Dacheng Li and Hao Zhang and Banghua Zhu and Michael Jordan and Joseph E. Gonzalez and Ion Stoica},
    year={2024},
    eprint={2403.04132},
    archivePrefix={arXiv},
    primaryClass={cs.AI}
}
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