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license: apache-2.0
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---
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license: apache-2.0
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language:
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- en
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base_model:
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- Qwen/Qwen2.5-0.5B
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---
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## Model Description
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This Memory Decoder model is trained on the Law domain and can be adapted to enhance any model in the Qwen2 and Qwen2.5 families.
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**Paper:** [Memory Decoder: A Pretrained, Plug-and-Play Memory for Large Language Models](https://www.arxiv.org/abs/2508.09874)
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**GitHub:** [https://github.com/LUMIA-Group/MemoryDecoder](https://github.com/LUMIA-Group/MemoryDecoder/tree/main)
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## Training & Evaluation Data
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**Law Domain Dataset:** [AsyLex](https://huggingface.co/datasets/clairebarale/AsyLex)
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**Test Split:** [MemoryDecoder-domain-data](https://huggingface.co/datasets/Clover-Hill/MemoryDecoder-domain-data)
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## Performance Results
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### Qwen2 Family
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| Model | Base Model | Base + MemDec |
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|-------|------------|---------------|
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| Qwen2-0.5B | 10.23 | 4.57 |
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| Qwen2-1.5B | 7.69 | 4.32 |
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| Qwen2-7B | 5.92 | 4.00 |
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| Qwen2-72B | 4.84 | 3.69 |
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### Qwen2.5 Family
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| Model | Base Model | Base + MemDec |
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|-------|------------|---------------|
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| Qwen2.5-0.5B | 9.86 | 4.57 |
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| Qwen2.5-1.5B | 7.42 | 4.29 |
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| Qwen2.5-3B | 6.68 | 4.16 |
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| Qwen2.5-7B | 5.94 | 4.01 |
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| Qwen2.5-14B | 5.35 | 3.86 |
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| Qwen2.5-32B | 5.18 | 3.81 |
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| Qwen2.5-72B | 4.84 | 3.70 |
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*Perplexity scores on Law domain test set. Lower is better.*
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## Citation
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```bibtex
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@article{cao2025memory,
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title={Memory decoder: A pretrained, plug-and-play memory for large language models},
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author={Cao, Jiaqi and Wang, Jiarui and Wei, Rubin and Guo, Qipeng and Chen, Kai and Zhou, Bowen and Lin, Zhouhan},
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journal={arXiv preprint arXiv:2508.09874},
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year={2025}
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}
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```
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## Contact
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For questions and support: [email protected]
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