---
title: "Xiangchi Yuan — author profile and papers — Elamur Research"
description: "Xiangchi Yuan, Georgia Institute of Technology: 6 papers on Elamur Research (2025–2026), h-index 2 — affiliations, topics, co-authors and…"
canonical: "https://research.elamur.ai/free/en/authors/xiangchi-yuan/"
---
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# Xiangchi Yuan

Xiangchi Yuan has 6 papers in our library, in 2025–2026, most of them on [Language models & pretraining](https://md.research.elamur.ai/free/en/topics/language-models/), [Reasoning](https://md.research.elamur.ai/free/en/topics/reasoning/), [Vision & language](https://md.research.elamur.ai/free/en/topics/multimodal/); often with [Chunhui Zhang](https://md.research.elamur.ai/free/en/authors/chunhui-zhang/), [Soroush Vosoughi](https://md.research.elamur.ai/free/en/authors/soroush-vosoughi/), [Zheyuan Liu](https://md.research.elamur.ai/free/en/authors/zheyuan-liu/).

6 papers in our library · 2025–2026

[OpenAlex](https://openalex.org/A5072246587) · [ORCID](https://orcid.org/0000-0001-5270-4817) · [**h-index 2**](https://openalex.org/authors/A5072246587) · [15 works](https://openalex.org/works?filter=author.id:A5072246587) · [51 citations](https://openalex.org/works?filter=author.id:A5072246587&sort=cited_by_count:desc) OpenAlex, 2026-10-14

[📄 6 works in our library](https://md.research.elamur.ai/free/en/authors/xiangchi-yuan/#papers) · [🔗 Cited 29 times in our library](https://md.research.elamur.ai/free/en/authors/xiangchi-yuan/cited-by/) · [1 more in our library without a page yet](#also) · [⭐ Paper Stars ranking: #8328](https://md.research.elamur.ai/free/en/paper-stars/page/84/#star-8328)

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=Xiangchi+Yuan) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Xiangchi+Yuan) · [dblp](https://dblp.org/search?q=Xiangchi+Yuan) · [ACL Anthology](https://aclanthology.org/search/?q=Xiangchi+Yuan)

## Affiliations

[🎓**Georgia Institute of Technology** Atlanta · United States 2024–2026 · 8 papers*current*](https://md.research.elamur.ai/free/en/universities/georgia-institute-of-technology/)

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 1 more institution on single bylines are not listed.

## Fields, topics and concepts

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

📚 Shelves 8 The field of science this work belongs to (OpenAlex fields).[Computer Science · 6 works](https://md.research.elamur.ai/free/en/shelves/computer-science/) · [Artificial Intelligence · 6 works](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/) · [Arts and Humanities · 5 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/) · [Language and Linguistics · 5 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/language-and-linguistics/) · [Computer Vision and Pattern Recognition · 3 works](https://md.research.elamur.ai/free/en/shelves/computer-science/computer-vision-and-pattern-recognition/) · [Social Sciences · 1 work](https://md.research.elamur.ai/free/en/shelves/social-sciences/) · [Computational Theory and Mathematics · 1 work](https://md.research.elamur.ai/free/en/shelves/computer-science/computational-theory-and-mathematics/) · [Education · 1 work](https://md.research.elamur.ai/free/en/shelves/social-sciences/education/)

🧭 Topics 6 Research subjects and languages the work is about.[Language models & pretraining · 4 works](https://md.research.elamur.ai/free/en/topics/language-models/) · [Reasoning · 2 works](https://md.research.elamur.ai/free/en/topics/reasoning/) · [Vision & language · 2 works](https://md.research.elamur.ai/free/en/topics/multimodal/) · [Efficient models & compression · 1 work](https://md.research.elamur.ai/free/en/topics/efficient-models/) · [Bias, fairness & safety · 1 work](https://md.research.elamur.ai/free/en/topics/bias-fairness-safety/) · [Dialogue systems · 1 work](https://md.research.elamur.ai/free/en/topics/dialogue-systems/)

## Works by year

### 2020s

[**2026** 3 papers](https://md.research.elamur.ai/free/en/authors/xiangchi-yuan/year/2026/) · [**2025** 3 papers](https://md.research.elamur.ai/free/en/authors/xiangchi-yuan/year/2025/)

## Papers

The most cited first (OpenAlex and our library).

1. **[Modality-Aware Neuron Pruning for Unlearning in Multimodal Large Language Models](https://md.research.elamur.ai/free/en/papers/liu-2025-modality-aware-neuron-pruning-unlearning/)** *(2025 · 12 citations)* Multimodal large language models can memorize private information, and erasing it is harder than in text-only LLMs.
2. **[Superficial Self-Improved Reasoners Benefit from Model Merging](https://md.research.elamur.ai/free/en/papers/yuan-2025-superficial-self-improved-reasoners-benefit/)** *(2025 · 8 citations)* Self-improvement, where a language model is fine-tuned on reasoning traces it generated itself, is often proposed as a remedy for scarce high-quality data.
3. **[Growing Through Experience: Scaling Episodic Grounding in Language Models](https://md.research.elamur.ai/free/en/papers/zhang-2025-growing-through-experience-scaling-episodic/)** *(2025 · 5 citations)* The paper addresses how language models can learn from past interaction experience (episodic grounding) to plan physical, multi-step tasks.
4. **[What Makes a Good Curriculum? Disentangling the Effects of Data Ordering on LLM Mathematical Reasoning](https://md.research.elamur.ai/free/en/papers/jia-2026-what-makes-good-curriculum-disentangling/)** *(2026 · 4 citations)* Curriculum learning, which sorts training examples from easy to hard, is often used to improve LLM reasoning.
5. **[Behavior Knowledge Merge in Reinforced Agentic Models](https://md.research.elamur.ai/free/en/papers/yuan-2026-behavior-knowledge-merge-reinforced-agentic/)** *(2026 · 3 citations)* The paper tackles how to combine several agents, each specialized through reinforcement learning (RL), into one generalist model without further training.
6. **[MTMCS-Bench: Evaluating Contextual Safety of Multimodal Large Language Models in Multi-Turn Dialogues](https://md.research.elamur.ai/free/en/papers/liu-2026-mtmcs-bench-evaluating-contextual-safety/)** *(2026 · 1 citation)* Most safety benchmarks for multimodal large language models (MLLMs) test one image–prompt pair at a time. They miss harmful intent that builds up over a conversation or that is stated early and then hidden behind innocent follow-ups. MTMCS-Bench fills this gap with three-turn dialogues grounded in COCO-style images.…

## All works

7 works of theirs in our library, the most cited first; 6 with a page here, the others link their original until we summarise them.

1. **[Modality-Aware Neuron Pruning for Unlearning in Multimodal Large Language Models](https://md.research.elamur.ai/free/en/papers/liu-2025-modality-aware-neuron-pruning-unlearning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zheyuan Liu, Guangyao Dou, Xiangchi Yuan, et al.*2025 · 12 citations*
2. **[Superficial Self-Improved Reasoners Benefit from Model Merging](https://md.research.elamur.ai/free/en/papers/yuan-2025-superficial-self-improved-reasoners-benefit/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Xiangchi Yuan, Chunhui Zhang, Zheyuan Liu, et al.*2025 · 8 citations*
3. **[Growing Through Experience: Scaling Episodic Grounding in Language Models](https://md.research.elamur.ai/free/en/papers/zhang-2025-growing-through-experience-scaling-episodic/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Chunhui Zhang, Sirui Wang, Zhongyu Ouyang, et al.*2025 · 5 citations*
4. **[What Makes a Good Curriculum? Disentangling the Effects of Data Ordering on LLM Mathematical Reasoning](https://md.research.elamur.ai/free/en/papers/jia-2026-what-makes-good-curriculum-disentangling/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yaning Jia, Chunhui Zhang, Xingjian Diao, et al.*2026 · 4 citations*
5. **[Behavior Knowledge Merge in Reinforced Agentic Models](https://md.research.elamur.ai/free/en/papers/yuan-2026-behavior-knowledge-merge-reinforced-agentic/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xiangchi Yuan, Dachuan Shi, Chunhui Zhang, et al.*2026 · 3 citations*
6. **[MTMCS-Bench: Evaluating Contextual Safety of Multimodal Large Language Models in Multi-Turn Dialogues](https://md.research.elamur.ai/free/en/papers/liu-2026-mtmcs-bench-evaluating-contextual-safety/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zheyuan Liu, Dongwhi Kim, Yixin Wan, et al.*2026 · 1 citation*
7. **[Inference-Time Control for Trustworthy Large Language Models ↗](https://doi.org/10.20944/preprints202605.1041.v1) Preprints.org · no summary yet**Yuyang Bai et al.*2026*

## Co-authors here

12 of 14 co-authors with a page, the most papers together first.

- [Chunhui Zhang](https://md.research.elamur.ai/free/en/authors/chunhui-zhang/) ×5
- [Soroush Vosoughi](https://md.research.elamur.ai/free/en/authors/soroush-vosoughi/) ×4
- [Zheyuan Liu](https://md.research.elamur.ai/free/en/authors/zheyuan-liu/) ×4
- [Dachuan Shi](https://md.research.elamur.ai/free/en/authors/dachuan-shi/) ×2
- [Meng Jiang](https://md.research.elamur.ai/free/en/authors/meng-jiang/) ×2
- [Wenke Lee](https://md.research.elamur.ai/free/en/authors/wenke-lee/) ×2
- [Zhaoxuan Tan](https://md.research.elamur.ai/free/en/authors/zhaoxuan-tan/) ×2
- [Zhongyu Ouyang](https://md.research.elamur.ai/free/en/authors/zhongyu-ouyang/) ×2
- [Chiyu Ma](https://md.research.elamur.ai/free/en/authors/chiyu-ma/)
- [Fengran Mo](https://md.research.elamur.ai/free/en/authors/fengran-mo/)
- [Guangyao Dou](https://md.research.elamur.ai/free/en/authors/guangyao-dou/)
- [Sirui Wang](https://md.research.elamur.ai/free/en/authors/sirui-wang/)

## 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/) ×2, [ACL 2025](https://md.research.elamur.ai/free/en/venues/acl/2025/) ×2
- [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/): [EMNLP 2025](https://md.research.elamur.ai/free/en/venues/emnlp/2025/)
- [Findings of the Association for Computational Linguistics](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/)
- Preprints.org

## Cited by

Papers of our library cite their works 29 times (of the 149,439 papers whose bibliographies we read); [13 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/xiangchi-yuan/cited-by/).

Updated 31 October 2026