| --- |
| license: odc-by |
| task_categories: |
| - text-generation |
| - question-answering |
| language: |
| - en |
| tags: |
| - synthetic |
| - sft |
| - instruction-tuning |
| - education |
| size_categories: |
| - 100K<n<1M |
| configs: |
| - config_name: math |
| data_files: math.parquet |
| - config_name: general_knowledge |
| data_files: general_knowledge.parquet |
| --- |
| |
| # LittleCurriculum-Chat |
|
|
| Synthetic K–5 chat data generated with Gemini 2.5 Flash and filtered with the |
| [LittleCurriculum filter](https://github.com/littlelearner-ll/littlecurriculum-filter). |
| Used to train the [LittleLearner](https://huggingface.co/littlelearner) models. |
|
|
| | Config | Rows | Seeded from | Content | |
| |---|---|---|---| |
| | `math` | 79,543 | MegaMath-Web-Pro-Max | Word problems with step-by-step worked solutions | |
| | `general_knowledge` | 484,787 | [LittleCurriculum](https://huggingface.co/datasets/littlelearner/LittleCurriculum) | Reading comprehension, factual QA, explanation, summarisation, definitions | |
|
|
| Seeds are real documents rather than topic prompts, which keeps the topic |
| distribution broad. The seed documents are not included here, so some questions |
| assume context the reader does not have ("what is the main idea of this |
| article?"). `seed_id` is the FineWeb-Edu document id, so the source text can be |
| recovered by joining against |
| [LittleCurriculum](https://huggingface.co/datasets/littlelearner/LittleCurriculum). |
|
|
| Every row carries a `messages` column in `[{role, content}]` form alongside the |
| structured fields. |
|
|
| ```python |
| from datasets import load_dataset |
| ds = load_dataset("littlelearner/LittleCurriculum-Chat", "general_knowledge") |
| ``` |
|
|
| ## Related data |
|
|
| For instruction fine-tuning we additionally used SmolTalk, MMLU |
| auxiliary-train and GSM8K, each filtered with our pipeline. For GRPO we used |
| grade-stratified synthetic problems from the MathCAMPS pipeline alongside |
| GSM8K, again filtered with our pipeline. We do not redistribute these — they |
| derive from public datasets and reproduce in one command: |
|
|
| ```bash |
| python filter_k5.py --hf-dataset HuggingFaceTB/smol-smoltalk --out smoltalk_k5.parquet |
| ``` |
|
|
| In our runs this data was most useful mixed into pretraining and midtraining |
| rather than reserved for a dedicated SFT stage. |
|
|
| ## License |
|
|
| ODC-By 1.0, inherited from FineWeb-Edu via LittleCurriculum. Generated with |
| Google Gemini. |
|
|
| ## Citation |
|
|
| ```bibtex |
| @misc{li2026littlelearner, |
| title={LittleLearner: Language Models Under Pedagogically Controlled Knowledge Exposure}, |
| author={Fanfei Li and Jana Zeller and Manuel Prada-Corral and Thaddäus Wiedemer and Prasanna Mayilvahanan and Ryan Cotterell and Wieland Brendel}, |
| year={2026}, |
| eprint={2608.13545}, |
| archivePrefix={arXiv}, |
| primaryClass={cs.CL}, |
| url={https://arxiv.org/abs/2608.13545}, |
| } |
| ``` |
|
|
