---
title: "Tong Ruan — papers of 2026 — 5 papers, the most cited first"
description: "Tong Ruan — papers of 2026: 5 papers on Elamur Research, the most cited first — what each work is about in our own words."
canonical: "https://research.elamur.ai/free/en/authors/tong-ruan/year/2026/"
---
[Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/tong-ruan/year/2026/)

[home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / [Tong Ruan](https://md.research.elamur.ai/free/en/authors/tong-ruan/) / 2026

# Tong Ruan — papers of 2026 — 5 papers, the most cited first

5 papers · [all years of Tong Ruan](https://md.research.elamur.ai/free/en/authors/tong-ruan/#years)

**[AIDA-SEAT: Towards Reliable AI Doctor Assistant via State-Evaluation-Action Tree Enhanced LLMs in Online Hospital](https://md.research.elamur.ai/free/en/papers/sun-2026-aida-seat-reliable-ai-doctor/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Lianxin Sun, Xiaoying Ying, Guangya Yu, et al.*2026*

**[Balancing Knowledge Breadth and Task Depth for Effective Domain Adaptation Fine-Tuning](https://md.research.elamur.ai/free/en/papers/zhang-2026-balancing-knowledge-breadth-task-depth/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Mu Zhang, Yuxiang Chu, Guangya Yu, et al.*2026*

**[Experience is the Teacher: Reusing Atomic Thoughts from LLMs to Improve Medical Dialogue](https://md.research.elamur.ai/free/en/papers/yu-2026-experience-is-teacher-reusing-atomic/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Guangya Yu, Hui Luo, Qi Ye, et al.*2026*

**[MCLE-Mol: Empowering LLM with Molecular Comprehension and Low-Cost Continual Evolution for Interpretable Property Prediction](https://md.research.elamur.ai/free/en/papers/pu-2026-mcle-mol-empowering-llm-molecular/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhili Pu, Lantian Zhang, Hao Duan, et al.*2026*

**[MedKInstruct: A Multimodal Knowledge Graph Based Framework for Multi-Hop and Hard-Negative Instruction Data Synthesis in MedVQA](https://md.research.elamur.ai/free/en/papers/wu-2026-medkinstruct-multimodal-knowledge-graph-based/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yinan Wu, Jihang Jin, Xuhao Bao, et al.*2026*