---
title: "Thoughts Are All Over the Place — paper by Mi; and Yu (2025)"
description: "To measure it, the authors propose an underthinking metric that captures how token-efficient incorrect… 27 references, cited by 60 papers here."
authors: ["Yue Wang; Qiuzhi Liu; Jiahao Xu; Tian Liang; Xingyu Chen; Zhiwei He; Linfeng Song; Dian Yu; Juntao Li; Zhuosheng Zhang; Rui Wang; Zhaopeng Tu; Haitao Mi;", "Dong Yu"]
year: 2025
venue: "arXiv:2501.18585"
source: "https://arxiv.org/abs/2501.18585"
doi: "10.48550/arxiv.2501.18585"
arxiv: "2501.18585"
licence: "arXiv — non-exclusive license to distribute"
licence_url: "http://arxiv.org/licenses/nonexclusive-distrib/1.0/"
summary_licence: "Elamur Cosmic License"
canonical: "https://research.elamur.ai/free/en/papers/wang-2025-thoughts-all-over-place-underthinking/"
---
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# Thoughts Are All Over the Place: On the Underthinking of o1-Like LLMs

**Authors:** Yue Wang; Qiuzhi Liu; Jiahao Xu; Tian Liang; Xingyu Chen; Zhiwei He; Linfeng Song; Dian Yu; Juntao Li; Zhuosheng Zhang; Rui Wang; Zhaopeng Tu; Haitao Mi; and [Dong Yu](https://md.research.elamur.ai/free/en/authors/dong-yu/) · **Year:** 2025 · **Venue:** arXiv:2501.18585 · **Licence:** [arXiv — non-exclusive license to distribute](http://arxiv.org/licenses/nonexclusive-distrib/1.0/)

**Links:** [Publisher's page](https://arxiv.org/abs/2501.18585) · [PDF](https://arxiv.org/pdf/2501.18585) · [DOI 10.48550/arxiv.2501.18585](https://doi.org/10.48550/arxiv.2501.18585) · [arXiv 2501.18585](https://arxiv.org/abs/2501.18585) · [OpenAlex](https://openalex.org/W4407012610)

**Citations:** 0 citations (OpenAlex, 2026-10-14) · [60](https://md.research.elamur.ai/free/en/papers/wang-2025-thoughts-all-over-place-underthinking/cited-by/) in our library, of the 149,439 papers whose bibliographies we read

## Summary
The paper examines a failure mode of o1-style reasoning models that the authors call "underthinking": the model keeps jumping to new solution strategies before it has fully pursued the current one. The study analyzes two open-source models with visible long chains of thought, QwQ-32B-Preview and DeepSeek-R1-671B, plus DeepSeek-R1-Preview. They are tested on MATH500, GPQA Diamond and AIME problems. A "thought" is treated as one reasoning segment, and a new one begins at markers such as "alternatively".

Failed answers turn out to be much longer and contain far more strategy switches than successful ones. This pattern grows stronger as problems get harder. To measure it, the authors propose an underthinking metric that captures how token-efficient incorrect responses are. As a remedy they introduce TIP, a decoding-time thought switching penalty that lowers the probability of switch tokens. This pushes the model to develop each line of reasoning more deeply. TIP raises accuracy on the hard test sets without any fine-tuning, which makes it a cheap fix that can be applied directly at inference.

## Key points
- Compared with correct responses, incorrect ones use about 225% more tokens on average, driven by roughly 418% more frequent thought switching.
- The benchmarks are:
  - MATH500, with difficulty levels 1–5;
  - GPQA Diamond, 198 questions;
  - AIME 2024, 30 problems, extended with 60 more from AIME 2022–2023.
- DeepSeek-R1-Preview was evaluated only on MATH500 and AIME because of a web-interface limit of 50 messages per day.
- In one illustrative case, QwQ-32B-Preview produced 25 separate thoughts within a single solution and still gave a wrong final answer.
- TIP is a training-free decoding strategy that penalizes thought-switching tokens. Conventional LLMs such as Qwen-Math-72B and Llama3.3-70B show no comparable length gap between their correct and incorrect answers.

*Our summary of the paper, in our own words — not its text. The work belongs to its authors; read it at the links above.*

## Institutions

- [Shanghai Jiao Tong University](https://md.research.elamur.ai/free/en/universities/shanghai-jiao-tong-university/) — University, Shanghai, China · 232 works · 20,305 citations
- [Tencent](https://md.research.elamur.ai/free/en/companies/tencent/) — Company, Shenzhen, China · 174 works · 21,355 citations
- [Soochow University](https://md.research.elamur.ai/free/en/universities/soochow-university/) — University, Suzhou, China · 71 works · 4,889 citations

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🧭 Topics (1): [🧠 Language models & pretraining](https://md.research.elamur.ai/free/en/topics/language-models/) · 4,145 works

## Cite

Cite as: Yue Wang; Qiuzhi Liu; Jiahao Xu; Tian Liang; Xingyu Chen; Zhiwei He; Linfeng Song; Dian Yu; Juntao Li; Zhuosheng Zhang; Rui Wang; Zhaopeng Tu; Haitao Mi; and Dong Yu. 2025. Thoughts Are All Over the Place: On the Underthinking of o1-Like LLMs. arXiv:2501.18585.

The paper itself, not this page. BibTeX from the library's record of the work.

```bibtex
@misc{mi2025thoughts,
  title = {{Thoughts Are All Over the Place: On the Underthinking of o1-Like LLMs}},
  author = {Yue Wang; Qiuzhi Liu; Jiahao Xu; Tian Liang; Xingyu Chen; Zhiwei He; Linfeng Song; Dian Yu; Juntao Li; Zhuosheng Zhang; Rui Wang; Zhaopeng Tu; Haitao Mi; and Dong Yu},
  year = {2025},
  doi = {10.48550/arxiv.2501.18585},
  eprint = {2501.18585},
  archivePrefix = {arXiv},
  url = {https://doi.org/10.48550/arxiv.2501.18585}
}
```

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## References

27 references, 15 of them with a card of ours. ↗ leads to the work, «find» searches for one we have no id for yet.

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*Updated 3 November 2026*