---
pretty_name: MemFactory
license: cc-by-sa-4.0
language:
- en
task_categories:
- question-answering
tags:
- long-context
- evaluation
- question-answering
- multi-hop
- hotpotqa
- synthetic
configs:
- config_name: eval_50
  data_files:
  - split: train
    path: eval_50.json
- config_name: eval_100
  data_files:
  - split: train
    path: eval_100.json
- config_name: converted_hotpotqa_2000
  data_files:
  - split: train
    path: converted_hotpotqa_2000.json
- config_name: eval_fwe_16384
  data_files:
  - split: train
    path: eval_fwe_16384.json
---


# MemFactory

## Overview

This repository provides a lightweight, derivative release of data used in **MemFactory**.

To evaluate the effectiveness of MemFactory, we reuse and adapt data from the upstream dataset:

- [`BytedTsinghua-SIA/hotpotqa`](https://huggingface.co/datasets/BytedTsinghua-SIA/hotpotqa)

This repository includes four JSON files:

- `eval_50.json`
- `eval_100.json`
- `eval_fwe_16384.json`
- `converted_hotpotqa_2000.json`

### Data Sources

- The three evaluation files are directly derived from the upstream HotpotQA-based release.
- The training file `converted_hotpotqa_2000.json` is a **locally adapted version** of the upstream training data, modified for MemFactory experiments.

For full dataset context, please refer to the upstream release:
- https://huggingface.co/datasets/BytedTsinghua-SIA/hotpotqa

---


## Limitations

- This is a **derivative redistribution**, not the original dataset.
- The data may inherit:
  - annotation noise  
  - biases  
  - structural limitations  
  from the upstream sources.
- `eval_fwe_16384.json` follows a **different schema** from the QA-style files.
- For full documentation and broader coverage, users should consult the upstream dataset.

---

## License

This repository is released under **CC BY-SA 4.0**.

**Reason:**

- The data is derived from the upstream HotpotQA-based dataset, which uses the same license.
- `converted_hotpotqa_2000.json` is an adapted derivative and must preserve share-alike terms.

If you use or redistribute this repository:
- Please retain attribution to the upstream source  
- Preserve the same license  

---

## Loading with 🤗 datasets

```python
from datasets import load_dataset

eval_50 = load_dataset("nworats/MemFactory", "eval_50", split="train")
eval_100 = load_dataset("nworats/MemFactory", "eval_100", split="train")
train_converted = load_dataset("nworats/MemFactory", "converted_hotpotqa_2000", split="train")
eval_fwe_16384 = load_dataset("nworats/MemFactory", "eval_fwe_16384", split="train")
````


## Citation

If you use this dataset, please cite:

### MemFactory (this work)

*(Placeholder – replace with your paper when available)*

```bibtex
@article{memfactory2025,
  title={MemFactory: [Your Subtitle Here]},
  author={Your Name et al.},
  journal={arXiv preprint arXiv:XXXX.XXXXX},
  year={2025}
}
```

### Upstream MemAgent work

```bibtex
@article{yu2025memagent,
  title={MemAgent: Reshaping Long-Context LLM with Multi-Conv RL-based Memory Agent},
  author={Yu, Hongli and others},
  journal={arXiv preprint arXiv:2507.02259},
  year={2025}
}
```