NewsReX: A More Efficient Approach to News Recommendation with Keras 3 and JAX
Paper β’ 2508.21572 β’ Published
NAML news recommendation model trained on MIND-small using the NewsReX framework (PYTORCH).
| Seed | AUC | MRR | NDCG@5 | NDCG@10 |
|---|---|---|---|---|
| 123 | 0.6636 | 0.3100 | 0.3439 | 0.4081 |
| 42 * | 0.6673 | 0.3117 | 0.3501 | 0.4122 |
| 456 | 0.6653 | 0.3096 | 0.3453 | 0.4089 |
| mean Β± std | 0.6654Β±0.0015 | 0.3105Β±0.0009 | 0.3464Β±0.0027 | 0.4097Β±0.0018 |
* Best seed (weights at repo root)
model:
name: naml
architecture:
news_encoder:
type: cnn_multi_view
views:
title:
type: cnn
filter_num: 400
kernel_size: 3
activation: relu
attention_query_dim: 200
abstract:
type: cnn
filter_num: 400
kernel_size: 3
activation: relu
attention_query_dim: 200
category:
type: embedding
embedding_dim: 100
subcategory:
type: embedding
embedding_dim: 100
view_attention_query_dim: 200
user_encoder:
type: additive_attention
attention_query_dim: 200
num_attention_heads: 10
click_predictor:
type: dot_product
embedding:
size: 300
trainable: true
dropout_rate: 0.2
seed: 42
inputs:
title:
max_length: 32
abstract:
max_length: 50
history:
max_length: 50
impressions:
max_length: 5
process_title: true
process_abstract: true
process_category: true
process_subcategory: true
process_user_id: false
training:
loss:
name: categorical_crossentropy
from_logits: true
reduction: sum_over_batch_size
label_smoothing: 0.0
optimizer: adam
learning_rate: 0.0001
batch_size: 256
num_epochs: 20
early_stopping:
patience: 5
min_improvement: 0.01
negative_sampling:
strategy: random
candidates: 4
evaluation:
mode: fast
metrics:
- auc
- mrr
- ndcg@5
- ndcg@10
batch_size: 512
newsrex/NAML-PYTORCH-MIND-small/
βββ model.safetensors β best seed (42)
βββ test_results.json
βββ training_run_summary.json
βββ seed_123/model.safetensors
βββ seed_42/model.safetensors
βββ seed_456/model.safetensors
βββ README.md
git clone https://github.com/igor17400/NewsReX.git
cd NewsReX && uv sync
# Run evaluation with best seed weights
uv run python src/eval.py \
experiment=mind/naml \
framework=pytorch \
weights=hf://newsrex/NAML-PYTORCH-MIND-small/model.safetensors
# Run evaluation with a specific seed
uv run python src/eval.py \
experiment=mind/naml \
framework=pytorch \
weights=hf://newsrex/NAML-PYTORCH-MIND-small/seed_42/model.safetensors
@misc{newsrex2026,
title={NewsReX: An Open-Source Multi-Framework for Neural News Recommendation},
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},
}