---
title: "A Self-Evolving LLM Agent Framework for Role-Based Norm"
description: "The authors propose a self-evolving agent whose identity has three parts: a role, a vector of communicator traits seeded from… 37 references."
authors: ["Haijie Ruan", "Xiaowu Jiang", "Zhanpeng LI", "Wei Jia", "Xuanwu Xu", "Xiao-Fen Shan", "Shujie Chen", "Xindong Ye"]
year: 2026
venue: "Findings of the Association for Computational Linguistics: ACL 2026"
source: "https://aclanthology.org/2026.findings-acl.1133/"
doi: "10.18653/v1/2026.findings-acl.1133"
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/ruan-2026-self-evolving-llm-agent-framework/"
---
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# A Self-Evolving LLM Agent Framework for Role-Based Norm Compliance in Healthcare

**Authors:** Haijie Ruan, Xiaowu Jiang, Zhanpeng LI, [Wei Jia](https://md.research.elamur.ai/free/en/authors/wei-jia/), Xuanwu Xu, Xiao-Fen Shan, Shujie Chen and Xindong Ye · **Year:** 2026 · **Venue:** [Findings of the Association for Computational Linguistics: ACL 2026](https://md.research.elamur.ai/free/en/venues/findings/) ([Findings of the Association for Computational Linguistics 2026](https://md.research.elamur.ai/free/en/venues/findings/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.findings-acl.1133/) · [PDF](https://aclanthology.org/2026.findings-acl.1133.pdf) · [DOI 10.18653/v1/2026.findings-acl.1133](https://doi.org/10.18653/v1/2026.findings-acl.1133) · [OpenAlex](https://openalex.org/W7166818071)

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

## Summary
The paper addresses a weakness of LLM agents in clinical role-play. Roles are usually fixed prompts and safety relies on one-off filters, so problems that build up over many turns slip through. Examples include missed escalation, a trainee overstepping scope, and gradual style drift. The authors propose a self-evolving agent whose identity has three parts: a role, a vector of communicator traits seeded from survey-based priors, and a context-dependent style. Role duties are encoded as hard IF–THEN norms with severity levels 1–5, while traits act only as soft preferences. The agent logs norm-annotated trajectories in structured memory. It then reflects on two time scales: quick diagnosis of responsibility errors, and longer-term checks for identity drift. Finally, it rewrites its prompts and identity parameters through preference-style optimization using AI feedback. Tests in a simulated multi-role hospital setting covered medication review, emergency triage and discharge planning. The full agent lowered severity-weighted norm risk and generally improved coordination and trust-like scores over static baselines. This points toward safer long-horizon behaviour for agents in high-stakes settings.

## Key points
- The environment is a partially observable multi-role setting with DOCTOR, NURSE, ADMIN and TRAINEE roles. Candidate replies are ranked by a weighted mix of a norm-violation penalty and trait alignment, so hard norms always override style.
- The full agent was compared with three baselines: Plain LLM, Norm-Instructed and Reflection-only. Aggregated ablation deltas in severity-weighted norm risk (SNR) were −2.83, −2.39 and −1.31 respectively. Gains in the trust-like signal (TSS) were +1.53, +1.20 and +0.55.
- On a 1–10 scale, the full agent's coordination score (CBS) on the second task was 7.22, against 5.22 for Plain LLM. However, its TSS on the first task (6.78) was slightly below Reflection-only (6.89).
- Embedding-based identity consistency (ICS) gave mixed results. The authors argue that stricter norm enforcement changes surface wording even when role adherence (RAR) improves.
- The work uses only simulation and no real patient data. Many metrics rely on rubric-guided LLM judges, and the norm set and severity weights are modelling choices rather than clinically complete rules.

*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

- [East China Normal University](https://md.research.elamur.ai/free/en/universities/east-china-normal-university/) — University, Shanghai, China · 50 works · 2,174 citations

Also on the byline: [Wenzhou University](https://ror.org/020hxh324).

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## Cite

Cite as: Haijie Ruan, Xiaowu Jiang, Zhanpeng LI, Wei Jia, Xuanwu Xu, Xiao-Fen Shan, Shujie Chen and Xindong Ye. 2026. A Self-Evolving LLM Agent Framework for Role-Based Norm Compliance in Healthcare. Findings of the Association for Computational Linguistics: ACL 2026.

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

```bibtex
@inproceedings{ruan2026self,
  title = {{A Self-Evolving LLM Agent Framework for Role-Based Norm Compliance in Healthcare}},
  author = {Haijie Ruan, Xiaowu Jiang, Zhanpeng LI, Wei Jia, Xuanwu Xu, Xiao-Fen Shan, Shujie Chen and Xindong Ye},
  booktitle = {Findings of the Association for Computational Linguistics: ACL 2026},
  year = {2026},
  doi = {10.18653/v1/2026.findings-acl.1133},
  url = {https://doi.org/10.18653/v1/2026.findings-acl.1133}
}
```

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*Updated 1 November 2026*