---
license: mit
task_categories:
- text-generation
tags:
- reasoning
- self-evolution
---

# INFUSER Qwen3-8B-base Artifacts

This dataset contains raw INFUSER Qwen3-8B-base generator output artifacts for steps 0, 30, 60, and 90, as presented in the paper [INFUSER: Influence-Guided Self-Evolution Improves Reasoning](https://huggingface.co/papers/2606.09052).

[**Paper**](https://huggingface.co/papers/2606.09052) | [**Code**](https://github.com/FFishy-git/INFUSER) | [**Blog**](https://y-agent.github.io/infuser)

## Artifact Information

- **Source run path**: `qwen3_8b_base/FW-Alr_2e-6-Glr_4e-6-DrGRPO-TIS_token-dev_800-precond_cos-seed456`
- **Source model/run context**: INFUSER Qwen3-8B-base generator outputs from training config `FW-Alr_2e-6-Glr_4e-6-DrGRPO-TIS_token-dev_800-precond_cos-seed456`.
- **Related model repo**: `Siyuc/INFUSER-Qwen3-8B-base`

### Files
The repository contains the following `.pt` files at the root:
- `gen_output_step000.pt`
- `gen_output_step030.pt`
- `gen_output_step060.pt`
- `gen_output_step090.pt`

## Usage
These `.pt` files are raw `DataProto` torch artifacts. They can be converted to question JSON using the project code's `derive_gen_questions()` function after loading the `DataProto` artifact. In the [official codebase](https://github.com/FFishy-git/INFUSER), see `verl_inf_evolve/utils/data_utils.py` for implementation details.

## Citation
```bibtex
@misc{chen2026infuser,
  title        = {INFUSER: Influence-Guided Self-Evolution Improves Reasoning},
  author       = {Siyu Chen and Miao Lu and Beining Wu and Heejune Sheen and Fengzhuo Zhang and Shuangning Li and Zhiyuan Li and Jose Blanchet and Tianhao Wang and Zhuoran Yang},
  year         = {2026},
  eprint       = {2606.09052},
  archivePrefix = {arXiv},
  primaryClass = {cs.LG},
  url          = {https://arxiv.org/abs/2606.09052}
}
```