| --- |
| license: apache-2.0 |
| language: |
| - zh |
| - en |
| - es |
| - fr |
| - de |
| - ru |
| - ja |
| - ko |
| base_model: |
| - Qwen/Qwen3-Embedding-4B |
| library_name: transformers |
| --- |
| # Querit-Reranker-4B |
|
|
| ## HighLights |
| Querit-Reranker-4B is a cross-encoder reranking model developed by the Querit family for multilingual text ranking tasks. |
| The model is initialized from Qwen3-Embedding-4B and further adapted for reranking through task-oriented post-training. |
| By jointly encoding each query-document pair, Querit-Reranker-4B captures fine-grained relevance signals and produces accurate ranking scores for second-stage retrieval. |
| With multilingual supervision, teacher-score distillation, and task-specific checkpoint merging, the model achieves strong performance across multilingual, English, and Chinese reranking benchmarks. |
|
|
|
|
| ### Model Description |
|
|
| <!-- Provide a longer summary of what this model is. --> |
|
|
|
|
| - **Model type:** Text Reranking |
| - **Language(s) (NLP):** Multilingual (Chinese, English, Spanish, French, German, Russian, Korean, Japanese) |
| - **Training Stage:** Pretraining & Post-training |
| - **Number of Total Parameters:** 4.02B |
| - **Number of Paramaters (Non-Embedding):** 3.63B |
| - **Number of Layers:** 36 |
| - **Number of Attention Heads:** 32 |
| - **Context Length:** 128k |
|
|
| ## Citation |
|
|
| If you find Querit-Reranker useful for your research or applications, please cite our paper: |
|
|
| **Querit-Reranker: Training Compact Multilingual Rerankers via Efficient Label-Free Distribution Adaptation** |
| Yunfei Zhong, Jun Yang, Wei Huang, Yinqiong Cai, Haosheng Qian, Yixing Fan, Ruqing Zhang, Lixin Su, Daiting Shi, and Jiafeng Guo. |
| arXiv:2606.19037, 2026. |
|
|
| ```bibtex |
| @misc{zhong2026queritrerankertrainingcompactmultilingual, |
| title={Querit-Reranker: Training Compact Multilingual Rerankers via Efficient Label-Free Distribution Adaptation}, |
| author={Yunfei Zhong and Jun Yang and Wei Huang and Yinqiong Cai and Haosheng Qian and Yixing Fan and Ruqing Zhang and Lixin Su and Daiting Shi and Jiafeng Guo}, |
| year={2026}, |
| eprint={2606.19037}, |
| archivePrefix={arXiv}, |
| primaryClass={cs.IR}, |
| url={https://arxiv.org/abs/2606.19037}, |
| } |
| ``` |
|
|
