--- title: "Xiaoran Fan · Fudan University — author profile and papers" description: "Xiaoran Fan, Fudan University: 5 papers on Elamur Research (2023–2026), h-index 15 — affiliations, topics, co-authors and who cites them…" canonical: "https://research.elamur.ai/free/en/authors/xiaoran-fan/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/xiaoran-fan/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Xiaoran Fan # Xiaoran Fan Xiaoran Fan has 5 papers in our library, in 2023–2026, most of them on [Language models & pretraining](https://md.research.elamur.ai/free/en/topics/language-models/), [Evaluation & benchmarks](https://md.research.elamur.ai/free/en/topics/evaluation-benchmarks/), [Reasoning](https://md.research.elamur.ai/free/en/topics/reasoning/); often with [Zhiheng Xi](https://md.research.elamur.ai/free/en/authors/zhiheng-xi/), [Enyu Zhou](https://md.research.elamur.ai/free/en/authors/enyu-zhou/), [Junjie Ye](https://md.research.elamur.ai/free/en/authors/junjie-ye/). 5 papers in our library · 2023–2026 [OpenAlex](https://openalex.org/A5101588749) · [ORCID](https://orcid.org/0000-0002-6368-9250) · [Wikidata](https://www.wikidata.org/wiki/Q131009278) · [**h-index 15**](https://openalex.org/authors/A5101588749) · [80 works](https://openalex.org/works?filter=author.id:A5101588749) · [1,572 citations](https://openalex.org/works?filter=author.id:A5101588749&sort=cited_by_count:desc) OpenAlex, 2026-10-14 [📄 5 works in our library](https://md.research.elamur.ai/free/en/authors/xiaoran-fan/#papers) · [🔗 Cited 548 times in our library](https://md.research.elamur.ai/free/en/authors/xiaoran-fan/cited-by/) · [3 more in our library without a page yet](#also) · [⭐ Paper Stars ranking: #1931](https://md.research.elamur.ai/free/en/paper-stars/page/20/#star-1931) 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=Xiaoran+Fan) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Xiaoran+Fan) · [dblp](https://dblp.org/search?q=Xiaoran+Fan) · [ACL Anthology](https://aclanthology.org/search/?q=Xiaoran+Fan) ## Affiliations [🎓**Fudan University** Shanghai · China 2023–2026 · 18 papers*current*](https://md.research.elamur.ai/free/en/universities/fudan-university/) · [🏢**Google** Mountain View · United States 2022–2025 · 18 papers](https://md.research.elamur.ai/free/en/companies/google/) · [🎓**Rutgers, The State University of New Jersey** New Brunswick · United States 2016–2022 · 12 papers](https://md.research.elamur.ai/free/en/universities/rutgers-the-state-university-of-new-jersey/) · [🎓**University of Chinese Academy of Sciences** Beijing · China 2022 · 2 papers](https://md.research.elamur.ai/free/en/universities/university-of-chinese-academy-of-sciences/) 🏛️**Rutgers University New Brunswick** New Brunswick · [United States](https://md.research.elamur.ai/free/en/countries/united-states/) 2016–2020Education 2016–2020 · Ph.D, Electrical and Computer Engineering 🏛️**Google LLC** Irvine · [United States](https://md.research.elamur.ai/free/en/countries/united-states/) Employment · Research Scientist, Health and Home From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 7 more institutions 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 · 5 works](https://md.research.elamur.ai/free/en/shelves/computer-science/) · [Artificial Intelligence · 5 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/) · [Engineering · 1 work](https://md.research.elamur.ai/free/en/shelves/engineering/) · [Computer Vision and Pattern Recognition · 1 work](https://md.research.elamur.ai/free/en/shelves/computer-science/computer-vision-and-pattern-recognition/) · [Control and Systems Engineering · 1 work](https://md.research.elamur.ai/free/en/shelves/engineering/control-and-systems-engineering/) · [Information Systems · 1 work](https://md.research.elamur.ai/free/en/shelves/computer-science/information-systems/) 🧭 Topics 3 Research subjects and languages the work is about.[Language models & pretraining · 3 works](https://md.research.elamur.ai/free/en/topics/language-models/) · [Evaluation & benchmarks · 1 work](https://md.research.elamur.ai/free/en/topics/evaluation-benchmarks/) · [Reasoning · 1 work](https://md.research.elamur.ai/free/en/topics/reasoning/) 💡 Concepts 1 Key ideas and methods explained on our concept pages.[Large language models · 1 work](https://md.research.elamur.ai/free/en/concepts/large-language-models/) ## Works by year ### 2020s [**2026** 2 papers](https://md.research.elamur.ai/free/en/authors/xiaoran-fan/year/2026/) · [**2025** 1 paper](https://md.research.elamur.ai/free/en/authors/xiaoran-fan/year/2025/) · [**2024** 1 paper](https://md.research.elamur.ai/free/en/authors/xiaoran-fan/year/2024/) · [**2023** 1 paper](https://md.research.elamur.ai/free/en/authors/xiaoran-fan/year/2023/) ## Papers The most cited first (OpenAlex and our library). 1. **[The Rise and Potential of Large Language Model Based Agents: A Survey](https://md.research.elamur.ai/free/en/papers/xi-2023-rise-potential-large-language/)** *(2023 · 1,272 citations)* This 2023 survey from the Fudan NLP Group maps the young field of agents built on large language models. The authors argue that earlier agent research mostly tuned algorithms for narrow skills, such as symbolic reasoning or board games like Go and Chess. What the field lacked was a general base model that agents… 2. **[LoRAMoE: Alleviating World Knowledge Forgetting in Large Language Models via MoE-Style Plugin](https://md.research.elamur.ai/free/en/papers/dou-2024-loramoe-alleviating-world-knowledge-forgetting/)** *(2024 · 93 citations)* The paper examines a trade-off in supervised fine-tuning (SFT) of LLMs. Adding much more instruction data keeps improving downstream tasks, but it also erodes the factual knowledge the model gained in pre-training. The authors build a 5-million-sample instruction set covering seven task categories and fine-tune… 3. **[ToolEyes: Fine-Grained Evaluation for Tool Learning Capabilities of Large Language Models in Real-world Scenarios](https://md.research.elamur.ai/free/en/papers/ye-2025-tooleyes-fine-grained-evaluation-tool/)** *(2025 · 35 citations)* Most benchmarks for tool use by large language models only check whether a model picks the expected API. That approach works only when correct answers can be fixed in advance, and it reveals little about the skills behind successful tool use. ToolEyes addresses both gaps. The authors define seven realistic scenarios… 4. **[Feedback-Driven Tool-Use Improvements in Large Language Models via Automated Build Environments](https://md.research.elamur.ai/free/en/papers/ye-2026-feedback-driven-tool-use-improvements/)** *(2026 · 6 citations)* Training LLMs to call tools with reinforcement learning is difficult for two reasons. Online APIs make training environments unstable and costly to maintain, and judging trajectories usually requires a strong LLM as evaluator, which brings bias. The authors propose FTRL, which removes both problems. An automated… 5. **[Which Reasoning Trajectories Teach Students to Reason Better? A Simple Metric of Informative Alignment](https://md.research.elamur.ai/free/en/papers/yang-2026-which-reasoning-trajectories-teach-students/)** *(2026 · 4 citations)* Distilling reasoning from a teacher LLM into a student through SFT on long chain-of-thought (CoT) traces does not reliably improve with teacher strength. ## All works 8 works of theirs in our library, the most cited first; 5 with a page here, the others link their original until we summarise them. 1. **[The Rise and Potential of Large Language Model Based Agents: A Survey](https://md.research.elamur.ai/free/en/papers/xi-2023-rise-potential-large-language/) [Science China Information Sciences](https://md.research.elamur.ai/free/en/venues/science-china-information-sciences/)**Zhiheng Xi, Wenxiang Chen, Xin Guo, et al.*2023 · 1,272 citations* 2. **[LoRAMoE: Alleviating World Knowledge Forgetting in Large Language Models via MoE-Style Plugin](https://md.research.elamur.ai/free/en/papers/dou-2024-loramoe-alleviating-world-knowledge-forgetting/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shihan Dou, Enyu Zhou, Yan Liu, et al.*2024 · 93 citations* 3. **[Secrets of RLHF in Large Language Models Part II: Reward Modeling ↗](https://arxiv.org/abs/2401.06080) arXiv:2401.06080 · no summary yet**Binghai Wang et al.*2024 · 72 citations* 4. **[Training Large Language Models for Reasoning through Reverse Curriculum Reinforcement Learning ↗](https://arxiv.org/abs/2402.05808) arXiv:2402.05808 · no summary yet**Zhiheng Xi et al.*2024 · 36 citations* 5. **[ToolEyes: Fine-Grained Evaluation for Tool Learning Capabilities of Large Language Models in Real-world Scenarios](https://md.research.elamur.ai/free/en/papers/ye-2025-tooleyes-fine-grained-evaluation-tool/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Junjie Ye, Guanyu Li, SongYang Gao, et al.*2025 · 35 citations* 6. **[StepCoder: Improving Code Generation with Reinforcement Learning from Compiler Feedback ↗](https://aclanthology.org/2024.acl-long.251/) Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · no summary yet**Shihan Dou et al.*2024 · 32 citations* 7. **[Feedback-Driven Tool-Use Improvements in Large Language Models via Automated Build Environments](https://md.research.elamur.ai/free/en/papers/ye-2026-feedback-driven-tool-use-improvements/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Junjie Ye, Changhao Jiang, Zhengyin Du, et al.*2026 · 6 citations* 8. **[Which Reasoning Trajectories Teach Students to Reason Better? A Simple Metric of Informative Alignment](https://md.research.elamur.ai/free/en/papers/yang-2026-which-reasoning-trajectories-teach-students/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yuming Yang, Mingyoung Lai, Wanxu Zhao, et al.*2026 · 4 citations* ## Co-authors here 12 of 33 co-authors with a page, the most papers together first. - [Zhiheng Xi](https://md.research.elamur.ai/free/en/authors/zhiheng-xi/) ×4 - [Enyu Zhou](https://md.research.elamur.ai/free/en/authors/enyu-zhou/) ×2 - [Junjie Ye](https://md.research.elamur.ai/free/en/authors/junjie-ye/) ×2 - [Qi Zhang](https://md.research.elamur.ai/free/en/authors/qi-zhang/) ×2 - [Shihan Dou](https://md.research.elamur.ai/free/en/authors/shihan-dou/) ×2 - [Songyang Gao](https://md.research.elamur.ai/free/en/authors/songyang-gao/) ×2 - [Tao Gui](https://md.research.elamur.ai/free/en/authors/tao-gui/) ×2 - [Xuanjing Huang](https://md.research.elamur.ai/free/en/authors/xuanjing-huang/) ×2 - [Caishuang Huang](https://md.research.elamur.ai/free/en/authors/caishuang-huang/) - [Haijun Lv](https://md.research.elamur.ai/free/en/authors/haijun-lv/) - [Jiecao Chen](https://md.research.elamur.ai/free/en/authors/jiecao-chen/) - [Jun Zhao](https://md.research.elamur.ai/free/en/authors/jun-zhao/) ## 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/) ×3: [ACL 2026](https://md.research.elamur.ai/free/en/venues/acl/2026/), [ACL 2024](https://md.research.elamur.ai/free/en/venues/acl/2024/) - [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/): [COLING 2025](https://md.research.elamur.ai/free/en/venues/coling/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/) - [Science China Information Sciences](https://md.research.elamur.ai/free/en/venues/science-china-information-sciences/): [Science China Information Sciences 2023](https://md.research.elamur.ai/free/en/venues/science-china-information-sciences/2023/) ## Cited by Papers of our library cite their works 548 times (of the 149,439 papers whose bibliographies we read); [112 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/xiaoran-fan/cited-by/). Updated 31 October 2026