README.md

---
title: NewsReX
emoji: 📰
colorFrom: blue
colorTo: purple
sdk: static
pinned: false
---

# NewsReX - News Recommendation Model Zoo

A modular, multi-framework benchmark for neural news recommendation research. All models are implemented in **JAX/Flax**, **PyTorch**, and **Keras 3**, trained and evaluated under identical conditions.

## Implemented Models

| Model | Paper | Venue | JAX | PyTorch | Keras |
|-------|-------|-------|-----|---------|-------|
| NRMS | [Wu et al.](https://aclanthology.org/D19-1671/) | EMNLP 2019 | ✅ | ✅ | ✅ |
| NAML | [Wu et al.](https://www.ijcai.org/proceedings/2019/536) | IJCAI 2019 | ✅ | ✅ | ✅ |
| LSTUR | [An et al.](https://aclanthology.org/P19-1033/) | ACL 2019 | ✅ | ✅ | ✅ |
| MINER | [Li et al.](https://aclanthology.org/2022.findings-acl.29/) | ACL Findings 2022 | ✅ | ✅ | ✅ |
| PP-Rec | [Qi et al.](https://aclanthology.org/2021.acl-long.34/) | ACL 2021 | ✅ | ✅ | ✅ |
| CAUM | [Qi et al.](https://dl.acm.org/doi/10.1145/3477495.3532040) | SIGIR 2022 | ✅ | ✅ | ✅ |
| CROWN | [Ko et al.](https://dl.acm.org/doi/10.1145/3696410.3714774) | WWW 2025 | ✅ | ✅ | ✅ |
| DIGAT | [Mao et al.](https://aclanthology.org/2022.findings-emnlp.227/) | EMNLP Findings 2022 | ✅ | ✅ | ✅ |
| GLORY | [Yang et al.](https://dl.acm.org/doi/10.1145/3604915.3608788) | RecSys 2023 | ✅ | ✅ | ✅ |
| TCCM | [Qi et al.](https://dl.acm.org/doi/10.1145/3583780.3615186) | CIKM 2023 | ✅ | ✅ | ✅ |

## Quick Start

```bash
# Install
git clone https://github.com/igor17400/NewsReX.git
cd NewsReX
uv sync --extra all-cuda

# Train NRMS on MIND-small
uv run python src/train.py experiment=mind/nrms framework=jax

# Load pretrained weights from HuggingFace
uv run python src/train.py experiment=mind/nrms framework=jax \
    weights=hf://newsrex/NRMS-JAX-MIND-small/model.safetensors
```

## Repository

**GitHub**: [github.com/igor17400/NewsReX](https://github.com/igor17400/NewsReX)

## Citation

If you use NewsReX in your research, please cite:

```bibtex
@misc{azevedo2025newsrexefficientapproachnews,
      title={NewsReX: A More Efficient Approach to News Recommendation with Keras 3 and JAX},
      author={Igor L. R. Azevedo and Toyotaro Suzumura and Yuichiro Yasui},
      year={2025},
      eprint={2508.21572},
      archivePrefix={arXiv},
      primaryClass={cs.IR},
      url={https://arxiv.org/abs/2508.21572},
}
```