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  <!-- Provide a quick summary of the dataset. -->
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- This dataset card aims to be a base template for new datasets. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/datasetcard_template.md?plain=1).
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- ## Dataset Details
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- ### Dataset Description
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- <!-- Provide a longer summary of what this dataset is. -->
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- - **Curated by:** [More Information Needed]
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- - **Funded by [optional]:** [More Information Needed]
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- - **Shared by [optional]:** [More Information Needed]
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- - **Language(s) (NLP):** [More Information Needed]
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- - **License:** [More Information Needed]
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  ### Dataset Sources [optional]
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  <!-- Provide the basic links for the dataset. -->
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- - **Repository:** [More Information Needed]
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- - **Paper [optional]:** [More Information Needed]
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- - **Demo [optional]:** [More Information Needed]
 
 
 
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  ## Uses
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- <!-- Address questions around how the dataset is intended to be used. -->
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  ### Direct Use
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  <!-- This section describes suitable use cases for the dataset. -->
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- [More Information Needed]
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- ### Out-of-Scope Use
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- <!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. -->
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- [More Information Needed]
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- ## Dataset Structure
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- <!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. -->
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- [More Information Needed]
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- ## Dataset Creation
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- ### Curation Rationale
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- <!-- Motivation for the creation of this dataset. -->
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- [More Information Needed]
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- ### Source Data
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- <!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). -->
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- #### Data Collection and Processing
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- <!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. -->
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- #### Who are the source data producers?
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- <!-- This section describes the people or systems who originally created the data. It should also include self-reported demographic or identity information for the source data creators if this information is available. -->
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- [More Information Needed]
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- ### Annotations [optional]
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- <!-- If the dataset contains annotations which are not part of the initial data collection, use this section to describe them. -->
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- #### Annotation process
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- <!-- This section describes the annotation process such as annotation tools used in the process, the amount of data annotated, annotation guidelines provided to the annotators, interannotator statistics, annotation validation, etc. -->
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- #### Who are the annotators?
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- <!-- This section describes the people or systems who created the annotations. -->
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- #### Personal and Sensitive Information
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- <!-- State whether the dataset contains data that might be considered personal, sensitive, or private (e.g., data that reveals addresses, uniquely identifiable names or aliases, racial or ethnic origins, sexual orientations, religious beliefs, political opinions, financial or health data, etc.). If efforts were made to anonymize the data, describe the anonymization process. -->
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- ## Bias, Risks, and Limitations
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- <!-- This section is meant to convey both technical and sociotechnical limitations. -->
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- ### Recommendations
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- <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
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- Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.
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  ## Citation [optional]
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  **BibTeX:**
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- [More Information Needed]
 
 
 
 
 
 
 
 
 
 
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  **APA:**
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- ## Glossary [optional]
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- <!-- If relevant, include terms and calculations in this section that can help readers understand the dataset or dataset card. -->
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- ## More Information [optional]
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- ## Dataset Card Authors [optional]
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- ## Dataset Card Contact
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- [More Information Needed]
 
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+ The SemiEvol dataset is part of the broader work on semi-supervised fine-tuning for Large Language Models (LLMs). The dataset includes labeled and unlabeled data splits designed to enhance the reasoning capabilities of LLMs through a bi-level knowledge propagation and selection framework, as proposed in the paper [SemiEvol: Semi-supervised Fine-tuning for LLM Adaptation](https://arxiv.org/abs/2410.14745).
 
 
 
 
 
 
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+ ## Dataset Details
 
 
 
 
 
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  ### Dataset Sources [optional]
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+ - **Repository:**
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+ - https://huggingface.co/datasets/cais/mmlu
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+ - https://huggingface.co/datasets/TIGER-Lab/MMLU-Pro
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+ - https://huggingface.co/datasets/cais/mmlu;
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+ - https://huggingface.co/AdaptLLM;
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+ - **Paper [optional]:** https://huggingface.co/papers/2410.14745
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  ## Uses
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  ### Direct Use
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+ Please refer to https://github.com/luo-junyu/SemiEvol for evaluation instruction.
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  <!-- This section describes suitable use cases for the dataset. -->
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  ## Citation [optional]
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  **BibTeX:**
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+ ```BibTex
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+ @misc{luo2024semievol,
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+ title={SemiEvol: Semi-supervised Fine-tuning for LLM Adaptation},
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+ author={Junyu Luo and Xiao Luo and Xiusi Chen and Zhiping Xiao and Wei Ju and Ming Zhang},
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+ year={2024},
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+ eprint={2410.14745},
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+ archivePrefix={arXiv},
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+ primaryClass={cs.CL},
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+ url={https://arxiv.org/abs/2410.14745},
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+ }
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+ ```
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  **APA:**
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+ Luo, J., Luo, X., Chen, X., Xiao, Z., Ju, W., & Zhang, M. (2024). SemiEvol: Semi-supervised Fine-tuning for LLM Adaptation. ArXiv. https://arxiv.org/abs/2410.14745