| --- |
| language: |
| - en |
| license: apache-2.0 |
| task_categories: |
| - text-generation |
| tags: |
| - rag |
| - retrieval-augmented-generation |
| --- |
| |
| # SPARK Training Data |
|
|
| This repository contains the training data for **SPARK**, presented in the paper [SPARK: Adaptive Parametric Knowledge Participation for Faithful Retrieval-Augmented Generation](https://arxiv.org/abs/2606.27786). |
|
|
| - **Repository:** https://github.com/OpenBMB/SPARK |
| - **Paper:** https://arxiv.org/abs/2606.27786 |
|
|
| ## Dataset Description |
|
|
| SPARK is a lightweight framework for resolving knowledge conflicts in retrieval-augmented generation (RAG). With the backbone LLM frozen, its participation policy dynamically regulates layer-wise FFN contributions, determining when and to what extent parametric knowledge participates during generation. |
| This dataset contains the training data synthesized with [FlashRAG](https://github.com/RUC-NLPIR/FlashRAG) using [MRQA-Shared-Task-2019](https://github.com/mrqa/MRQA-Shared-Task-2019) to train the participation policy of SPARK. |
|
|
| ## Citation |
|
|
| If you find this work useful, please cite our paper: |
|
|
| ```bibtex |
| @misc{li2026sparkadaptiveparametricknowledge, |
| title={SPARK: Adaptive Parametric Knowledge Participation for Faithful Retrieval-Augmented Generation}, |
| author={Ruochang Li and Pengcheng Huang and Zhenghao Liu and Yukun Yan and Huiyuan Xie and Yu Gu and Ge Yu and Maosong Sun}, |
| year={2026}, |
| eprint={2606.27786}, |
| archivePrefix={arXiv}, |
| primaryClass={cs.CL}, |
| url={https://arxiv.org/abs/2606.27786}, |
| } |
| ``` |
