---
title: "Yu Tian · Tsinghua University — author profile and papers"
description: "Yu Tian, Tsinghua University: 8 papers on Elamur Research (2025–2026), h-index 0 — affiliations, topics, co-authors and who cites them in…"
canonical: "https://research.elamur.ai/free/en/authors/yu-tian/"
---
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# Yu Tian

Yu Tian has 8 papers in our library, in 2025–2026, most of them on [Language models & pretraining](https://md.research.elamur.ai/free/en/topics/language-models/), [Bias, fairness & safety](https://md.research.elamur.ai/free/en/topics/bias-fairness-safety/), [Reasoning](https://md.research.elamur.ai/free/en/topics/reasoning/); often with [Xue Yang](https://md.research.elamur.ai/free/en/authors/xue-yang/), [Jingyuan Zhang](https://md.research.elamur.ai/free/en/authors/jingyuan-zhang/), [Kaiwen Wei](https://md.research.elamur.ai/free/en/authors/kaiwen-wei/).

8 papers in our library · 2025–2026

[OpenAlex](https://openalex.org/A5139797151) · [**h-index 0**](https://openalex.org/authors/A5139797151) · [10 works](https://openalex.org/works?filter=author.id:A5139797151) · [0 citations](https://openalex.org/works?filter=author.id:A5139797151&sort=cited_by_count:desc) OpenAlex, 2026-10-14

[📄 8 works in our library](https://md.research.elamur.ai/free/en/authors/yu-tian/#papers) · [🔗 Cited 12 times in our library](https://md.research.elamur.ai/free/en/authors/yu-tian/cited-by/) · [⭐ Paper Stars ranking: #10872](https://md.research.elamur.ai/free/en/paper-stars/page/109/#star-10872)

The profile is the library's match of the name; two people with one name are not always told apart.

Elsewhere: [Google Scholar](https://scholar.google.com/citations?view_op=search_authors&mauthors=Yu+Tian) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Yu+Tian) · [dblp](https://dblp.org/search?q=Yu+Tian) · [ACL Anthology](https://aclanthology.org/search/?q=Yu+Tian)

## Affiliations

[🎓**Tsinghua University** Beijing · China 2025–2026 · 7 papers*current*](https://md.research.elamur.ai/free/en/universities/tsinghua-university/)

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine.

## Fields, topics and concepts

Of its works in our library, with the number of works on each.

📚 Shelves 14 The field of science this work belongs to (OpenAlex fields).[Computer Science · 8 works](https://md.research.elamur.ai/free/en/shelves/computer-science/) · [Computer Vision and Pattern Recognition · 3 works](https://md.research.elamur.ai/free/en/shelves/computer-science/computer-vision-and-pattern-recognition/) · [Artificial Intelligence · 7 works](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/) · [Arts and Humanities · 4 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/) · [Language and Linguistics · 4 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/language-and-linguistics/) · [Computer Networks and Communications · 1 work](https://md.research.elamur.ai/free/en/shelves/computer-science/computer-networks-and-communications/) · [Health Information Management · 1 work](https://md.research.elamur.ai/free/en/shelves/health-professions/health-information-management/) · [Health Professions · 1 work](https://md.research.elamur.ai/free/en/shelves/health-professions/) · [Human-Computer Interaction · 1 work](https://md.research.elamur.ai/free/en/shelves/computer-science/human-computer-interaction/) · [Information Systems · 1 work](https://md.research.elamur.ai/free/en/shelves/computer-science/information-systems/) · [Psychology · 1 work](https://md.research.elamur.ai/free/en/shelves/psychology/) · [Safety Research · 1 work](https://md.research.elamur.ai/free/en/shelves/social-sciences/safety-research/) · [Social Psychology · 1 work](https://md.research.elamur.ai/free/en/shelves/psychology/social-psychology/) · [Social Sciences · 1 work](https://md.research.elamur.ai/free/en/shelves/social-sciences/)

🧭 Topics 5 Research subjects and languages the work is about.[Bias, fairness & safety · 3 works](https://md.research.elamur.ai/free/en/topics/bias-fairness-safety/) · [Reasoning · 2 works](https://md.research.elamur.ai/free/en/topics/reasoning/) · [Language models & pretraining · 5 works](https://md.research.elamur.ai/free/en/topics/language-models/) · [Vision & language · 2 works](https://md.research.elamur.ai/free/en/topics/multimodal/) · [English · 1 work](https://md.research.elamur.ai/free/en/topics/english/)

## Works by year

### 2020s

[**2026** 7 papers](https://md.research.elamur.ai/free/en/authors/yu-tian/year/2026/) · [**2025** 1 paper](https://md.research.elamur.ai/free/en/authors/yu-tian/year/2025/)

## Papers

The most cited first (OpenAlex and our library).

1. **[Red Teaming Large Reasoning Models](https://md.research.elamur.ai/free/en/papers/chen-2026-red-teaming-large-reasoning-models/)** *(2026 · 7 citations)* Large Reasoning Models (LRMs) produce explicit chains of thought. This visible reasoning creates attack surfaces that standard LLM evaluations miss, and earlier benchmarks examined single threats in isolation without comparing LRMs to their base LLMs. The authors introduce Rt-LRM, a unified red-teaming benchmark that…
2. **[Seedream 2.0: A Native Chinese-English Bilingual Image Generation Foundation Model](https://md.research.elamur.ai/free/en/papers/gong-2025-seedream-2-0-native/)** *(2025 · 5 citations)* Seedream 2.0 is a text-to-image diffusion foundation model that natively accepts prompts in both Chinese and English.
3. **[DPN-LE: Dual Personality Neuron Localization and Editing for Large Language Models](https://md.research.elamur.ai/free/en/papers/zheng-2026-dpn-le-dual-personality-neuron/)** *(2026)* Neuron-editing approaches to steering the personality of large language models, such as NPTI, alter tens of thousands of MLP neurons per trait and harm general abilities.
4. **[Know Your Place: Diagnosing Implicit Social Adaptation Failures in Chinese Large Language Models](https://md.research.elamur.ai/free/en/papers/tian-2026-know-your-place-diagnosing-implicit/)** *(2026)* The paper asks whether Chinese LLMs adapt their conversational style to social signals that are only implied in a user's message, rather than stated in an instruction.
5. **[Me-Agent: A Personalized Mobile Agent with Two-Level User Habit Learning for Enhanced Interaction](https://md.research.elamur.ai/free/en/papers/wang-2026-me-agent-personalized-mobile-agent/)** *(2026)* LLM-driven phone agents usually execute only what the user states explicitly. They struggle when a request leaves out the app ("play some music") or the content ("play my favorite"), and they do not learn from a person's past behavior. Me-Agent addresses this without any fine-tuning by modeling user habits at two…
6. **[MentalSeek-Dx: Towards Progressive Hypothetico-Deductive Reasoning for Real-world Psychiatric Diagnosis](https://md.research.elamur.ai/free/en/papers/sun-2026-mentalseek-dx-progressive-hypothetico-deductive/)** *(2026)* The paper tackles automated psychiatric diagnosis with LLMs. Existing evaluation data are mostly social-media posts or synthetic stories with coarse labels, so they say little about real clinical use. The authors build MentalDx Bench from 712 de-identified electronic health records collected at partner hospitals.…
7. **[Safe-FedLLM: Delving into the Safety of Federated Large Language Models](https://md.research.elamur.ai/free/en/papers/tao-2026-safe-fedllm-delving-into-safety/)** *(2026)* Federated fine-tuning of LLMs (FedLLM) lets parties train jointly without pooling raw data. Little is known about how to defend such systems against malicious clients when the server sees only LoRA updates. The authors built a testbed on OpenFedLLM and FedLLM-Attack using Llama3.1-8B and Qwen2.5-7B. Benign clients…
8. **[SafeSteer: A Decoding-level Defense Mechanism for Multimodal Large Language Models](https://md.research.elamur.ai/free/en/papers/zeng-2026-safesteer-decoding-level-defense-mechanism/)** *(2026)* Multimodal LLMs are easier to jailbreak than text-only models, especially when the harmful content is hidden in an image.

## Co-authors here

12 of 32 co-authors with a page, the most papers together first.

- [Xue Yang](https://md.research.elamur.ai/free/en/authors/xue-yang/) ×4
- [Jingyuan Zhang](https://md.research.elamur.ai/free/en/authors/jingyuan-zhang/) ×3
- [Kaiwen Wei](https://md.research.elamur.ai/free/en/authors/kaiwen-wei/) ×3
- [Xinyi Zeng](https://md.research.elamur.ai/free/en/authors/xinyi-zeng/) ×3
- [Huanqian Yan](https://md.research.elamur.ai/free/en/authors/huanqian-yan/) ×2
- [Jiawei Chen](https://md.research.elamur.ai/free/en/authors/jiawei-chen/) ×2
- [Lifan Zheng](https://md.research.elamur.ai/free/en/authors/lifan-zheng/) ×2
- [Xiang Chen](https://md.research.elamur.ai/free/en/authors/xiang-chen/) ×2
- [Chang Liu](https://md.research.elamur.ai/free/en/authors/chang-liu/)
- [Chenyan WU](https://md.research.elamur.ai/free/en/authors/chenyan-wu/)
- [Fanheng Kong](https://md.research.elamur.ai/free/en/authors/fanheng-kong/)
- [Fei Liu](https://md.research.elamur.ai/free/en/authors/fei-liu/)

## Venues

Where their works here were published, the most works first, with the editions of those that have a page.

- [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/) ×4: [ACL 2026](https://md.research.elamur.ai/free/en/venues/acl/2026/) ×4
- [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/) ×3: [Findings of the Association for Computational Linguistics 2026](https://md.research.elamur.ai/free/en/venues/findings/2026/) ×3

## Cited by

Papers of our library cite their works 12 times (of the 149,439 papers whose bibliographies we read); [8 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/yu-tian/cited-by/).

Updated 2 November 2026
