---
dataset_info:
  splits:
    - name: biomed
    - name: law
    - name: finance
  features:
    - name: text
      type: string
license: apache-2.0
task_categories:
- text-generation
language:
- en
---
## Dataset Description

This dataset contains the test splits used to evaluate the Memory Decoder model across three specialized domains: biomedical, legal, and finance. 
The test data was randomly sampled from publicly available datasets to assess the model's performance in domain-specific language understanding.

**GitHub:** [https://github.com/LUMIA-Group/MemoryDecoder](https://github.com/LUMIA-Group/MemoryDecoder/tree/main)

## Dataset Sources

The test data is sampled randomly from the following source datasets:

### Biomedical Domain
- **Source:** [Medilora/mimic_iii_diagnosis_anonymous](https://huggingface.co/datasets/Medilora/mimic_iii_diagnosis_anonymous)
- **Description:** Anonymized clinical discharge summaries from the MIMIC-III database containing medical diagnoses, patient histories, and treatment procedures

### Legal Domain
- **Source:** [clairebarale/AsyLex](https://huggingface.co/datasets/clairebarale/AsyLex)
- **Description:** Refugee status determination documents from Canada (1996-2022) containing legal judgments and case analyses
- **Paper Reference:** [ACL 2023 Findings](https://aclanthology.org/2023.findings-acl.187)

### Finance Domain
- **Source:** [jyanimaulik/yahoo_finance_stockmarket_news](https://huggingface.co/datasets/jyanimaulik/yahoo_finance_stockmarket_news)
- **Description:** Stock market news articles from Yahoo Finance covering company earnings, market analysis, and financial commentary

## Dataset Structure

### Data Splits

The dataset consists of test splits only, randomly sampled from the source datasets:

```
├── biomed/     # Biomedical domain test split
├── law/        # Legal domain test split
└── finance/    # Finance domain test split
```

## Citation

```bibtex
@article{cao2025memory,
  title={Memory decoder: A pretrained, plug-and-play memory for large language models},
  author={Cao, Jiaqi and Wang, Jiarui and Wei, Rubin and Guo, Qipeng and Chen, Kai and Zhou, Bowen and Lin, Zhouhan},
  journal={arXiv preprint arXiv:2508.09874},
  year={2025}
}
```

## Contact

For questions and support: maximus.cao@outlook.com