--- title: "Fanqi Wan · Sun Yat-sen University — author profile and papers" description: "Fanqi Wan, Sun Yat-sen University: 6 papers on Elamur Research (2024–2026), h-index 6 — affiliations, topics, co-authors and who cites…" canonical: "https://research.elamur.ai/free/en/authors/fanqi-wan/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/fanqi-wan/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Fanqi Wan # Fanqi Wan Fanqi Wan has 6 papers in our library, in 2024–2026, most of them on [Reasoning](https://md.research.elamur.ai/free/en/topics/reasoning/), [Language models & pretraining](https://md.research.elamur.ai/free/en/topics/language-models/), [Dialogue systems](https://md.research.elamur.ai/free/en/topics/dialogue-systems/); often with [Xiaojun Quan](https://md.research.elamur.ai/free/en/authors/xiaojun-quan/), [Chengyuan Yao](https://md.research.elamur.ai/free/en/authors/chengyuan-yao/), [Jingcheng Hu](https://md.research.elamur.ai/free/en/authors/jingcheng-hu/). 6 papers in our library · 2024–2026 [OpenAlex](https://openalex.org/A5101262140) · [**h-index 6**](https://openalex.org/authors/A5101262140) · [31 works](https://openalex.org/works?filter=author.id:A5101262140) · [86 citations](https://openalex.org/works?filter=author.id:A5101262140&sort=cited_by_count:desc) OpenAlex, 2026-10-14 [📄 6 works in our library](https://md.research.elamur.ai/free/en/authors/fanqi-wan/#papers) · [🔗 Cited 117 times in our library](https://md.research.elamur.ai/free/en/authors/fanqi-wan/cited-by/) · [⭐ Paper Stars ranking: #7415](https://md.research.elamur.ai/free/en/paper-stars/page/75/#star-7415) 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=Fanqi+Wan) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Fanqi+Wan) · [dblp](https://dblp.org/search?q=Fanqi+Wan) · [ACL Anthology](https://aclanthology.org/search/?q=Fanqi+Wan) ## Affiliations [🎓**Sun Yat-sen University** Guangzhou · China 2022–2026 · 25 papers*current*](https://md.research.elamur.ai/free/en/universities/sun-yat-sen-university/) 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 5 The field of science this work belongs to (OpenAlex fields).[Computer Science · 6 works](https://md.research.elamur.ai/free/en/shelves/computer-science/) · [Arts and Humanities · 5 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/) · [Artificial Intelligence · 6 works](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/) · [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/) 🧭 Topics 4 Research subjects and languages the work is about.[Language models & pretraining · 1 work](https://md.research.elamur.ai/free/en/topics/language-models/) · [Reasoning · 3 works](https://md.research.elamur.ai/free/en/topics/reasoning/) · [Dialogue systems · 1 work](https://md.research.elamur.ai/free/en/topics/dialogue-systems/) · [Vision & language · 1 work](https://md.research.elamur.ai/free/en/topics/multimodal/) ## Works by year ### 2020s [**2026** 3 papers](https://md.research.elamur.ai/free/en/authors/fanqi-wan/year/2026/) · [**2025** 2 papers](https://md.research.elamur.ai/free/en/authors/fanqi-wan/year/2025/) · [**2024** 1 paper](https://md.research.elamur.ai/free/en/authors/fanqi-wan/year/2024/) ## Papers The most cited first (OpenAlex and our library). 1. **[Knowledge Fusion of Large Language Models](https://md.research.elamur.ai/free/en/papers/wan-2024-knowledge-fusion-large-language-models/)** *(2024 · 82 citations)* Training a strong LLM from scratch is very expensive and often reproduces abilities that existing models already have. 2. **[FuseChat: Knowledge Fusion of Chat Models](https://md.research.elamur.ai/free/en/papers/wan-2025-fusechat-knowledge-fusion-chat-models/)** *(2025 · 25 citations)* Building a strong chat LLM from scratch is expensive, and many existing models already have overlapping skills. 3. **[QwenLong-L1: Towards Long-Context Large Reasoning Models with Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/wan-2025-qwenlong-l1-long-context/)** *(2025 · 13 citations)* Reinforcement learning has made large reasoning models (LRMs) much better at problems with short inputs. It is still unclear how to train them to reason over very long documents, potentially around 120K tokens. The authors frame this as "long-context reasoning RL," where the model must first find and ground the… 4. **[PaCoRe: Learning to Scale Test-Time Compute with Parallel Coordinated Reasoning](https://md.research.elamur.ai/free/en/papers/hu-2026-pacore-learning-scale-test-time/)** *(2026 · 5 citations)* Language models that reason step by step in a single chain hit a hard limit: once the context window is full, reasoning must stop. 5. **[ProactiveEval: A Unified Evaluation Framework for Proactive Dialogue Agents](https://md.research.elamur.ai/free/en/papers/liu-2026-proactiveeval-unified-evaluation-framework-proactive/)** *(2026 · 3 citations)* Research on proactive dialogue agents, which start conversations and steer users toward goals without being asked, has been fragmented. 6. **[STEP3-VL-10B Technical Report](https://md.research.elamur.ai/free/en/papers/huang-2026-step3-vl-10b-technical/)** *(2026 · 2 citations)* Compact multimodal models (around 10B parameters or fewer) are usually efficient but weaker at difficult perception and reasoning. ## Co-authors here 12 of 24 co-authors with a page, the most papers together first. - [Xiaojun Quan](https://md.research.elamur.ai/free/en/authors/xiaojun-quan/) ×3 - [Chengyuan Yao](https://md.research.elamur.ai/free/en/authors/chengyuan-yao/) ×2 - [Jingcheng Hu](https://md.research.elamur.ai/free/en/authors/jingcheng-hu/) ×2 - [Ziyi Yang](https://md.research.elamur.ai/free/en/authors/ziyi-yang/) ×2 - [Ailin Huang](https://md.research.elamur.ai/free/en/authors/ailin-huang/) - [Chenliang Li](https://md.research.elamur.ai/free/en/authors/chenliang-li/) - [Chunrui Han](https://md.research.elamur.ai/free/en/authors/chunrui-han/) - [Deng Cai](https://md.research.elamur.ai/free/en/authors/deng-cai/) - [Fei Huang](https://md.research.elamur.ai/free/en/authors/fei-huang/) - [Hangyu Guo](https://md.research.elamur.ai/free/en/authors/hangyu-guo/) - [Ji Zhang](https://md.research.elamur.ai/free/en/authors/ji-zhang/) - [Jingren Zhou](https://md.research.elamur.ai/free/en/authors/jingren-zhou/) ## 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/) ×2: [ACL 2026](https://md.research.elamur.ai/free/en/venues/acl/2026/) ×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/) ## Cited by Papers of our library cite their works 117 times (of the 149,439 papers whose bibliographies we read); [33 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/fanqi-wan/cited-by/). Updated 2 November 2026