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@@ -47,12 +47,40 @@ dataset_info:
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  download_size: 121089
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  dataset_size: 186908
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  configs:
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- - config_name: corpus
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- data_files:
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- - split: train
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- path: corpus/train-*
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  - config_name: qa
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  data_files:
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  - split: train
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  path: qa/train-*
 
 
 
 
 
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  ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  download_size: 121089
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  dataset_size: 186908
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  configs:
 
 
 
 
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  - config_name: qa
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  data_files:
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  - split: train
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  path: qa/train-*
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+ - config_name: corpus
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+ data_files:
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+ - split: train
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+ path: corpus/train-*
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+
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  ---
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+ ## AutoRAG evaluation dataset
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+ ### Made with 2024 LLM resesarch articles (papers)
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+ This dataset is an example for [AutoRAG](https://github.com/Marker-Inc-Korea/AutoRAG).
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+ You can directly use this dataset for optimizng and benchmarking your RAG setup in AutoRAG.
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+
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+ ### How this dataset created?
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+ This dataset is 100% synthetically generated by GPT-4 and `Marker Inc.` technology.
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+ At first, we collected 110 latest LLM papers at arxiv.
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+ We used `Marker` OCR model to extract texts.
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+ And chunk it using MarkdownSplitter and TokenSplitter from Langchain.
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+ For more quality, we delete all `References` in the research articles.
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+ And then, it randomly select 520 passages from chunked corpus for generating question.
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+ At last, our custom pipeline generates various and unique questions with GPT-4.
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+ ## Acknowledgements
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+ This dataset's corpus is originated various LLM related research articles on arixv.
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+ Marker Inc. do not have copyright or any rights about corpus content itself.
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+ Plus, this is a alpha version of our evaluation data generation pipeline without human verification, so its quality might be lower than human-generated dataset.
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+