---
title: "Self-Reflective Generation at Test Time — Mu 2026"
description: "SRGen is a training-free, test-time alternative that intervenes before a risky token is committed. 41 references."
authors: ["Jian Mu", "Qixin Zhang", "Zhiyong Wang", "Menglin Yang", "Shuang Qiu", "Chengwei Qin", "Zhongxiang Dai", "Yao Shu"]
year: 2026
venue: "Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)"
source: "https://aclanthology.org/2026.acl-long.465/"
doi: "10.18653/v1/2026.acl-long.465"
licence: "CC BY 4.0 (ACL Anthology)"
licence_url: "https://creativecommons.org/licenses/by/4.0/"
summary_licence: "Elamur Cosmic License"
canonical: "https://research.elamur.ai/free/en/papers/mu-2026-self-reflective-generation-test-time/"
---
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# Self-Reflective Generation at Test Time

**Authors:** Jian Mu, Qixin Zhang, [Zhiyong Wang](https://md.research.elamur.ai/free/en/authors/zhiyong-wang/), [Menglin Yang](https://md.research.elamur.ai/free/en/authors/menglin-yang/), [Shuang Qiu](https://md.research.elamur.ai/free/en/authors/shuang-qiu/), [Chengwei Qin](https://md.research.elamur.ai/free/en/authors/chengwei-qin/), [Zhongxiang Dai](https://md.research.elamur.ai/free/en/authors/zhongxiang-dai/) and [Yao Shu](https://md.research.elamur.ai/free/en/authors/yao-shu/) · **Year:** 2026 · **Venue:** [Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)](https://md.research.elamur.ai/free/en/venues/acl/) ([ACL 2026](https://md.research.elamur.ai/free/en/venues/acl/2026/)) · **Publisher:** [Association for Computational Linguistics](https://md.research.elamur.ai/free/en/publishers/association-for-computational-linguistics/) · **Licence:** [CC BY 4.0 (ACL Anthology)](https://creativecommons.org/licenses/by/4.0/)

**Links:** [Publisher's page](https://aclanthology.org/2026.acl-long.465/) · [PDF](https://aclanthology.org/2026.acl-long.465.pdf) · [DOI 10.18653/v1/2026.acl-long.465](https://doi.org/10.18653/v1/2026.acl-long.465) · [OpenAlex](https://openalex.org/W4415981843)

**Citations:** 0 citations (OpenAlex, 2026-10-14)

## Summary
Autoregressive LLMs cannot revise a token once it is emitted, so one early mistake in a long chain-of-thought can derail the whole solution. Existing fixes either rewrite complete drafts afterwards or teach self-correction through costly training such as RL. Both act only after the error already exists. SRGen is a training-free, test-time alternative that intervenes before a risky token is committed. During decoding, it tracks next-token entropy and compares it with a threshold built from the mean and standard deviation of recent entropies. When that threshold is crossed, it briefly optimizes a small vector δ and adds it to the final hidden state. The optimization objective balances two goals: keeping the already generated prefix probable and sharpening the current prediction. Experiments on math reasoning, general reasoning and code across several LLMs show consistent accuracy gains with modest extra latency. The method also combines well with techniques such as SLOT. Its value lies in being a cheap plug-in for more reliable reasoning, although it requires white-box access to hidden states and gradients.

## Key points
- **Trigger rule.** Reflection starts when the current entropy exceeds μ + k·σ, computed over a sliding window of the last N token entropies. This makes the trigger adapt to each model's entropy profile.
- **Loss.** δ is trained with a hybrid loss L_SRGen = (1−λ)·L_CE + λ·L_AEM.
  - L_CE is a retrospective cross-entropy over the prefix, with δ applied to all past hidden states.
  - L_AEM is an entropy-minimization term.
- **Combination with SLOT** on Qwen2.5-Math-7B with greedy decoding:
  - MATH500: 63.8% → 70.6%
  - AMC: 35.0% → 38.0% (SRGen alone reaches 37.0%)
  - AIME2024: 13.3% → 30.0%
- **What gets flagged.** In DeepSeek-R1-Distill-Qwen-7B and DeepSeek-R1-Distill-Llama-8B on MATH500 and GPQA, flagged tokens are mostly function words and connectives (e.g., "so", "but", "maybe", "if"). These tend to sit at reasoning decision points.
- **Availability and limitations.** Code is released at github.com/2020-qqtcg/SRGen. Limitations include the need for white-box inference, extra hyperparameters, and position selection that could still be improved.

*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

- [University of Edinburgh](https://md.research.elamur.ai/free/en/universities/university-of-edinburgh/) — University, Edinburgh, United Kingdom · 381 works · 80,747 citations
- [Nanyang Technological University](https://md.research.elamur.ai/free/en/universities/nanyang-technological-university/) — University, Singapore, Singapore · 184 works · 27,484 citations
- [Chinese University of Hong Kong, Shenzhen](https://md.research.elamur.ai/free/en/universities/chinese-university-of-hong-kong-shenzhen/) — University, Shenzhen, China · 56 works · 3,212 citations
- [City University of Hong Kong](https://md.research.elamur.ai/free/en/universities/city-university-of-hong-kong/) — University, Hong Kong, China · 59 works · 3,480 citations
- [The Hong Kong University of Science and Technology (Guangzhou)](https://md.research.elamur.ai/free/en/universities/the-hong-kong-university-of-science-and-technology-guangzhou/) — University, Guangzhou, China · 67 works · 1,765 citations

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## Cite

Cite as: Jian Mu, Qixin Zhang, Zhiyong Wang, Menglin Yang, Shuang Qiu, Chengwei Qin, Zhongxiang Dai and Yao Shu. 2026. Self-Reflective Generation at Test Time. Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers).

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

```bibtex
@inproceedings{mu2026self,
  title = {{Self-Reflective Generation at Test Time}},
  author = {Jian Mu, Qixin Zhang, Zhiyong Wang, Menglin Yang, Shuang Qiu, Chengwei Qin, Zhongxiang Dai and Yao Shu},
  booktitle = {Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)},
  year = {2026},
  doi = {10.18653/v1/2026.acl-long.465},
  url = {https://doi.org/10.18653/v1/2026.acl-long.465}
}
```

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*Updated 2 November 2026*