Scaling Latent Reasoning via Looped Language Models
Paper • 2510.25741 • Published • 229
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Check out the documentation for more information.
First study of whether iterative latent computation helps machine translation, evaluated on WMT24++.
pip install -r requirements.txt
python train_ouro_2.6b.py
python train_qwen_3b.py
python eval_baseline.py
python eval_finetuned.py
python analyze_results.py
train_ouro_2.6b.py - QLoRA fine-tune Ouro-2.6Btrain_qwen_3b.py - QLoRA fine-tune Qwen2.5-3Beval_baseline.py - Phase 1: Baseline evaluationeval_finetuned.py - Phase 2: Fine-tuned evaluationanalyze_results.py - Phase 3: Analysisdavidmeikle/opus-translation-train-en-de-cs
@article{zhu2025scaling,
title={Scaling Latent Reasoning via Looped Language Models},
author={Zhu, Rui-Jie and others},
journal={arXiv preprint arXiv:2510.25741},
year={2025}
}