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ReflectRL Qwen2.5 Math 7B GRPO

This repository contains model weights trained using ReflectRL, as presented in the paper ReflectRL: Learning from Golden Negative Trajectories via Reflective-to-Direct Reasoning.

TypeText modelModèle de baseQwen2.5VersionmodelÉditeur@JinheCClasse

Source du modèle

Type
Text model
Taille du fichier
28,4 GB
Modèle de base
Qwen2.5
Version
vmodel
Mis à jour
4 oct. 2026
Éditeur
@Jinhe
Téléchargements
23
Paramètres
7B
Source
Hugging Face

Description de la source

ReflectRL: Learning from Golden Negative Trajectories via Reflective-to-Direct Reasoning

This repository contains model weights trained using ReflectRL, as presented in the paper ReflectRL: Learning from Golden Negative Trajectories via Reflective-to-Direct Reasoning.

Overview

ReflectRL is a lightweight framework for learning from Golden Negative Trajectories (GNTs) during on-policy post-training. Instead of imitating failed expert trajectories directly, ReflectRL uses them as reflective context during training and gradually transitions the policy back to direct reasoning for inference.

Citation

@article{reflectrl2027,
  title={ReflectRL: Learning from Golden Negative Trajectories via Reflective-to-Direct Reasoning},
  author={Jinhe Bi and Chennan Zhou and Zengjie Jin and Aniri and Shuo Lu and Wenke Huang and Hu Cao and Xun Xiao and Zhihong Zhu and Volker Tresp and Fei Shen and Yunpu Ma and Tat-Seng Chua},
  year={2027}
}

Sources

1 source
Hugging FacePrincipalVersion ef1a1f65b5a557944f5815af0cc6ea84bbace610
huggingface.co/Jinhe/ReflectRL-Qwen2.5-Math-7B-GRPO/tree/ef1a1f65b5a557944f5815af0cc6ea84bbace610

Vérifié 4 oct.

Artefacts du modèle

1 artefact

model.safetensors

safetensors · 28,4 GB · SHA-256 ad2350a0ca3f…bf2b · Hugging Face

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Extraits de sources

3 extraits

--- license: apache-2.0 library_name: transformers pipeline_tag: text-generation --- # ReflectRL: Learning from Golden Negative Trajectories via Reflective-to-Direct Reasoning This repository contains model weights trained using **ReflectRL**, as presented in the paper [ReflectRL: Learning from Golden Negative Trajectories via Reflective-to-Direct Reasoning](https://huggingface.co/papers/2608.03972). - **Paper:** [ReflectRL: Learning from Golden Negative Trajectories via Reflective-to-Direct Reasoning](https://huggingface.co/papers/2608.03972) - **Repository:** [GitHub - bibisbar/ReflectRL](https://github.com/bibisbar/ReflectRL) ## Overview ReflectRL is a lightweight framework for learning from Golden Negative Trajectories (GNTs) during on-policy post-training. Instead of imitating failed expert trajectories directly, ReflectRL uses them as reflective context during training and gradually transitions the policy back to direct reasoning for inference. ## Citation ```bibtex @article{reflectrl2027, title={ReflectRL: Learning from Golden Negative Trajectories via Reflective-to-Direct Reasoning}, author={Jinhe Bi and Chennan Zhou and Zengjie Jin and Aniri and Shuo Lu and Wenke Huang and Hu Cao and Xun Xiao and Zhihong Zhu and Volker Tresp and Fei Shen and Yunpu Ma and Tat-Seng Chua}, year={2027} } ```

Source context: 23 downloads · 0 likes · Pipeline text-generation · Library transformers · Repo Jinhe/ReflectRL-Qwen2.5-Math-7B-GRPO

Source context: 191 downloads · 0 likes · Repo Jinhe/ReflectRL-Qwen2.5-Math-7B-GRPO