---
title: "Achieving Gold-Medal-Level Olympiad Reasoning via Simple and Unified Scaling"
source: HuggingFace Daily Papers · 2026-05-17
url: https://arxiv.org/abs/2605.13301
date: 2026-05-18
published_at: 2026-05-17T12:00:00+00:00
tag: 论文研究
item_id: f53cd8fe8b64a6fb
---
# Computer Science > Artificial Intelligence

[Submitted on 13 May 2026]

# Title:Achieving Gold-Medal-Level Olympiad Reasoning via Simple and Unified Scaling

[View PDF](https://arxiv.org/pdf/2605.13301)

[HTML (experimental)](https://arxiv.org/html/2605.13301v1)

Abstract:Recent progress in reasoning models has substantially advanced long-horizon mathematical and scientific problem solving, with several systems now reaching gold-medal-level performance on International Mathematical Olympiad (IMO) and International Physics Olympiad (IPhO) problems. In this paper, we introduce a simple and unified recipe for converting a post-trained reasoning backbone into a rigorous olympiad-level solver. The recipe first uses a reverse-perplexity curriculum for SFT to instill rigorous proof-search and self-checking behaviors, then scales these behaviors through a two-stage RL pipeline that progresses from RL with verifiable rewards to more delicate proof-level RL, and finally boosts solving performance with test-time scaling. Applying this recipe, we train a 30B-A3B backbone with SFT on around 340K sub-8K-token trajectories followed by 200 RL steps. The resulting model, SU-01, supports stable reasoning on difficult problems with trajectories exceeding 100K tokens, while achieving gold-medal-level performance on mathematical and physical olympiad competitions, including IMO 2025/USAMO 2026 and IPhO 2024/2025. It also demonstrates strong generalization of scientific reasoning to domains beyond mathematics and physics.

### References & Citations

Loading...

# Bibliographic and Citation Tools

Bibliographic Explorer

*(*[What is the Explorer?](https://info.arxiv.org/labs/showcase.html#arxiv-bibliographic-explorer))
Connected Papers

*(*[What is Connected Papers?](https://www.connectedpapers.com/about))
Litmaps

*(*[What is Litmaps?](https://www.litmaps.co/))
scite Smart Citations

*(*[What are Smart Citations?](https://www.scite.ai/))# Code, Data and Media Associated with this Article

alphaXiv

*(*[What is alphaXiv?](https://alphaxiv.org/))
CatalyzeX Code Finder for Papers

*(*[What is CatalyzeX?](https://www.catalyzex.com))
DagsHub

*(*[What is DagsHub?](https://dagshub.com/))
Gotit.pub

*(*[What is GotitPub?](http://gotit.pub/faq))
Hugging Face

*(*[What is Huggingface?](https://huggingface.co/huggingface))
ScienceCast

*(*[What is ScienceCast?](https://sciencecast.org/welcome))# Demos

# Recommenders and Search Tools

Influence Flower

*(*[What are Influence Flowers?](https://influencemap.cmlab.dev/))
CORE Recommender

*(*[What is CORE?](https://core.ac.uk/services/recommender))# arXivLabs: experimental projects with community collaborators

arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website.

Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them.

Have an idea for a project that will add value for arXiv's community? [ Learn more about arXivLabs](https://info.arxiv.org/labs/index.html).