On the Interplay of Pre-Training, Mid-Training, and RL on Reasoning Language Models
Paper • 2512.07783 • Published • 39
This repository contains the context B pretraining checkpoints and the corresponding final RL checkpoints. In this setting, the teacher component uses only op2 during pretraining.
Only inference-relevant Hugging Face files are included.
Within each setting:
base/ stores the final op2-only pretraining checkpoint.rl/ stores the final RL checkpoints for each experiment variant.0.9zoo_op2-20+0.1teacher_op20.99zoo_op2-20+0.01teacher_op20.999zoo_op2-20+0.001teacher_op2from transformers import AutoModelForCausalLM, AutoTokenizer
repo_id = "Interplay-LM-Reasoning/context_pretrain_2"
subdir = "0.99zoo_op2-20+0.01teacher_op2/rl/contextzoo_0.99zoo_0.01teacher_process_strict"
tokenizer = AutoTokenizer.from_pretrained(repo_id, subfolder=subdir)
model = AutoModelForCausalLM.from_pretrained(repo_id, subfolder=subdir)
@misc{zhang2025interplaypretrainingmidtrainingrl,
title={On the Interplay of Pre-Training, Mid-Training, and RL on Reasoning Language Models},
author={Charlie Zhang and Graham Neubig and Xiang Yue},
year={2025},
eprint={2512.07783},
archivePrefix={arXiv},
primaryClass={cs.CL},
url={https://arxiv.org/abs/2512.07783},
}