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Xiaoran Fan

Xiaoran Fan has 5 papers in our library, in 2023–2026, most of them on Language models & pretraining, Evaluation & benchmarks, Reasoning; often with Zhiheng Xi, Enyu Zhou, Junjie Ye.

5 papers in our library · 2023–2026

OpenAlex · ORCID · Wikidata · h-index 15 · 80 works · 1,572 citations OpenAlex, 2026-10-14

📄 5 works in our library · 🔗 Cited 548 times in our library · 3 more in our library without a page yet · ⭐ Paper Stars ranking: #1931

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

Elsewhere: Google Scholar · Semantic Scholar · dblp · ACL Anthology

 Affiliations

🎓Fudan UniversityShanghai · China2023–2026 · 18 paperscurrent🏢GoogleMountain View · United States2022–2025 · 18 papers🎓Rutgers, The State University of New JerseyNew Brunswick · United States2016–2022 · 12 papers🎓University of Chinese Academy of SciencesBeijing · China2022 · 2 papers
🏛️Rutgers University New BrunswickNew Brunswick · United States2016–2020Education 2016–2020 · Ph.D, Electrical and Computer Engineering
🏛️Google LLCIrvine · United StatesEmployment · 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 8The field of science this work belongs to (OpenAlex fields).Computer Science · 5 worksArtificial Intelligence · 5 worksArts and Humanities · 4 worksLanguage and Linguistics · 4 worksEngineering · 1 workComputer Vision and Pattern Recognition · 1 workControl and Systems Engineering · 1 workInformation Systems · 1 work

🧭 Topics 3Research subjects and languages the work is about.Language models & pretraining · 3 worksEvaluation & benchmarks · 1 workReasoning · 1 work

💡 Concepts 1Key ideas and methods explained on our concept pages.Large language models · 1 work

 Works by year

2020s

20262 papers20251 paper20241 paper20231 paper

 Papers

The most cited first (OpenAlex and our library).

  1. The Rise and Potential of Large Language Model Based Agents: A Survey (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 (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 (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 (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 (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 SurveyScience China Information SciencesZhiheng Xi, Wenxiang Chen, Xin Guo, et al.2023 · 1,272 citations
  2. LoRAMoE: Alleviating World Knowledge Forgetting in Large Language Models via MoE-Style PluginAnnual Meeting of the Association for Computational Linguistics (ACL)Shihan Dou, Enyu Zhou, Yan Liu, et al.2024 · 93 citations
  3. Secrets of RLHF in Large Language Models Part II: Reward Modeling ↗arXiv:2401.06080 · no summary yetBinghai Wang et al.2024 · 72 citations
  4. Training Large Language Models for Reasoning through Reverse Curriculum Reinforcement Learning ↗arXiv:2402.05808 · no summary yetZhiheng Xi et al.2024 · 36 citations
  5. ToolEyes: Fine-Grained Evaluation for Tool Learning Capabilities of Large Language Models in Real-world ScenariosInternational Conference on Computational Linguistics (COLING)Junjie Ye, Guanyu Li, SongYang Gao, et al.2025 · 35 citations
  6. StepCoder: Improving Code Generation with Reinforcement Learning from Compiler Feedback ↗Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · no summary yetShihan Dou et al.2024 · 32 citations
  7. Feedback-Driven Tool-Use Improvements in Large Language Models via Automated Build EnvironmentsFindings of the Association for Computational LinguisticsJunjie Ye, Changhao Jiang, Zhengyin Du, et al.2026 · 6 citations
  8. Which Reasoning Trajectories Teach Students to Reason Better? A Simple Metric of Informative AlignmentAnnual Meeting of the Association for Computational Linguistics (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.

Venues

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

 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 →.

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