---
title: "Linxi Fan — author profile and papers — Elamur Research"
description: "Linxi Fan, Nvidia: 3 papers on Elamur Research (2022–2023), h-index 20 — affiliations, topics, co-authors and who cites them in our library."
canonical: "https://research.elamur.ai/free/en/authors/linxi-fan/"
---
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# Linxi Fan

Linxi Fan has 3 papers in our library, in 2022–2023, most of them on [Language models & pretraining](https://md.research.elamur.ai/free/en/topics/language-models/); often with [Anima Anandkumar](https://md.research.elamur.ai/free/en/authors/anima-anandkumar/), [De-An Huang](https://md.research.elamur.ai/free/en/authors/de-an-huang/), [Guanzhi Wang](https://md.research.elamur.ai/free/en/authors/guanzhi-wang/).

3 papers in our library · 2022–2023

[OpenAlex](https://openalex.org/A5054905472) · [**h-index 20**](https://openalex.org/authors/A5054905472) · [63 works](https://openalex.org/works?filter=author.id:A5054905472) · [3,513 citations](https://openalex.org/works?filter=author.id:A5054905472&sort=cited_by_count:desc) OpenAlex, 2026-10-14

[📄 3 works in our library](https://md.research.elamur.ai/free/en/authors/linxi-fan/#papers) · [🔗 Cited 1,447 times in our library](https://md.research.elamur.ai/free/en/authors/linxi-fan/cited-by/) · [36 more in our library without a page yet](#also) · [⭐ Paper Stars ranking: #4746](https://md.research.elamur.ai/free/en/paper-stars/page/48/#star-4746)

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

## Affiliations

[🏢**Nvidia** Santa Clara · United States 2022–2026 · 12 papers*current*](https://md.research.elamur.ai/free/en/companies/nvidia/) · [🏢**Nvidia** Reading · United Kingdom 2022–2025 · 8 papers](https://md.research.elamur.ai/free/en/companies/nvidia-united-kingdom/) · [🎓**Stanford University** Stanford · United States 2017–2022 · 5 papers](https://md.research.elamur.ai/free/en/universities/stanford-university/) · [🎓**Columbia University** New York · United States 2014–2017 · 4 papers](https://md.research.elamur.ai/free/en/universities/columbia-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 4 The field of science this work belongs to (OpenAlex fields).[Artificial Intelligence · 3 works](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/) · [Computer Science · 3 works](https://md.research.elamur.ai/free/en/shelves/computer-science/) · [Control and Systems Engineering · 1 work](https://md.research.elamur.ai/free/en/shelves/engineering/control-and-systems-engineering/) · [Engineering · 1 work](https://md.research.elamur.ai/free/en/shelves/engineering/)

🧭 Topics 1 Research subjects and languages the work is about.[Language models & pretraining · 2 works](https://md.research.elamur.ai/free/en/topics/language-models/)

## Works by year

### 2020s

[**2023** 1 paper](https://md.research.elamur.ai/free/en/authors/linxi-fan/year/2023/) · [**2022** 2 papers](https://md.research.elamur.ai/free/en/authors/linxi-fan/year/2022/)

## Papers

The most cited first (OpenAlex and our library).

1. **[MineDojo: Building Open-Ended Embodied Agents with Internet-Scale Knowledge](https://md.research.elamur.ai/free/en/papers/fan-2022-minedojo-building-open-ended-embodied/)** *(2022 · 149 citations)* Most embodied agents are trained from scratch in narrow environments with hand-designed objectives, so they rarely generalize to new goals.
2. **[Eureka: Human-Level Reward Design via Coding Large Language Models](https://md.research.elamur.ai/free/en/papers/ma-2023-eureka-human-level-reward-design/)** *(2023 · 142 citations)* Hand-crafting reward functions for reinforcement learning is slow, relies on trial and error, and often yields sub-optimal results.
3. **[Pre-Trained Language Models for Interactive Decision-Making](https://md.research.elamur.ai/free/en/papers/li-2022-pre-trained-language-models-interactive/)** *(2022 · 124 citations)* The paper asks whether language models trained only on text can serve as a backbone for sequential decision-making, even when the task involves no language.

## All works

39 works of theirs in our library, the most cited first; 3 with a page here, the others link their original until we summarise them.

1. **[Voyager: An Open-Ended Embodied Agent with Large Language Models ↗](https://arxiv.org/abs/2305.16291) arXiv:2305.16291 · no summary yet**Guanzhi Wang et al.*2023 · 639 citations*
2. [**MineDojo: Building Open-Ended Embodied Agents with Internet-Scale Knowledge arXiv:2206.08853**Linxi Fan, Guanzhi Wang, Yunfan Jiang, et al.*2022 · 149 citations*](https://md.research.elamur.ai/free/en/papers/fan-2022-minedojo-building-open-ended-embodied/)
3. [**Eureka: Human-Level Reward Design via Coding Large Language Models arXiv:2310.12931**Yecheng Jason Ma, William Liang, Guanzhi Wang, et al.*2023 · 142 citations*](https://md.research.elamur.ai/free/en/papers/ma-2023-eureka-human-level-reward-design/)
4. **[World of Bits: An Open-Domain Platform for Web-Based Agents ↗](https://openalex.org/W2741548518) International Conference on Machine Learning · no summary yet**Tianlin Shi et al.*2017 · 135 citations*
5. [**Pre-Trained Language Models for Interactive Decision-Making arXiv:2202.01771**Shuang Li, Xavier Puig, Chris Paxton, et al.*2022 · 124 citations*](https://md.research.elamur.ai/free/en/papers/li-2022-pre-trained-language-models-interactive/)
6. **[GR00T N1: An Open Foundation Model for Generalist Humanoid Robots ↗](https://arxiv.org/abs/2503.14734) arXiv:2503.14734 · no summary yet**NVIDIA et al.*2025 · 123 citations*
7. **[VIMA: General Robot Manipulation with Multimodal Prompts ↗](https://arxiv.org/abs/2210.03094) arXiv:2210.03094 · no summary yet**Yunfan Jiang et al.*2022 · 117 citations*
8. **[SURREAL: Open-Source Reinforcement Learning Framework and Robot Manipulation Benchmark ↗](https://openalex.org/W2899059606) Conference on Robot Learning · no summary yet**Linxi Fan et al.*2018 · 117 citations*
9. **[RubiksNet: Learnable 3D-Shift for Efficient Video Action Recognition ↗](https://doi.org/10.1007/978-3-030-58529-7_30) Lecture notes in computer science · no summary yet**Linxi Fan et al.*2020 · 69 citations*
10. **[ASAP: Aligning Simulation and Real-World Physics for Learning Agile Humanoid Whole-Body Skills ↗](https://doi.org/10.15607/rss.2025.xxi.066) arXiv:2502.01143 · no summary yet**Tairan He et al.*2025 · 62 citations*
11. **[LongVILA: Scaling Long-Context Visual Language Models for Long Videos ↗](https://arxiv.org/abs/2408.10188) arXiv:2408.10188 · no summary yet**Yukang Chen et al.*2024 · 49 citations*
12. **[DrEureka: Language Model Guided Sim-To-Real Transfer ↗](https://doi.org/10.15607/rss.2024.xx.094) arXiv:2406.01967 · no summary yet**Yecheng Jason Ma et al.*2024 · 44 citations*
13. **[Re-ViLM: Retrieval-Augmented Visual Language Model for Zero and Few-Shot Image Captioning ↗](https://aclanthology.org/2023.findings-emnlp.793/) Findings of the Association for Computational Linguistics: EMNLP 2023 · no summary yet**Zhuolin Yang et al.*2023 · 44 citations*
14. **[MimicPlay: Long-Horizon Imitation Learning by Watching Human Play ↗](https://arxiv.org/abs/2302.12422) arXiv (Cornell University) · no summary yet**Chen Wang et al.*2023 · 43 citations*
15. **[MimicGen: A Data Generation System for Scalable Robot Learning using Human Demonstrations ↗](https://arxiv.org/abs/2310.17596) arXiv (Cornell University) · no summary yet**Ajay Mandlekar et al.*2023 · 33 citations*
16. **[World Simulation with Video Foundation Models for Physical AI ↗](https://arxiv.org/abs/2511.00062) arXiv (Cornell University) · no summary yet**Nvidia Nvidia et al.*2025 · 16 citations*
17. **[DreamDojo: A Generalist Robot World Model from Large-Scale Human Videos ↗](https://arxiv.org/abs/2602.06949) arXiv (Cornell University) · no summary yet**Shenyuan Gao et al.*2026 · 15 citations*
18. **[FLARE: Robot Learning with Implicit World Modeling ↗](https://arxiv.org/abs/2505.15659) arXiv (Cornell University) · no summary yet**Ruijie Zheng et al.*2025 · 15 citations*
19. **[DreamGen: Unlocking Generalization in Robot Learning through Video World Models ↗](https://arxiv.org/abs/2505.12705) arXiv (Cornell University) · no summary yet**Joel Jang et al.*2025 · 12 citations*
20. **[AMAGO: Scalable In-Context Reinforcement Learning for Adaptive Agents ↗](https://arxiv.org/abs/2310.09971) arXiv (Cornell University) · no summary yet**Jake Grigsby, Linxi Fan, Yuke Zhu*2023 · 8 citations*
21. **[CaP-X: A Framework for Benchmarking and Improving Coding Agents for Robot Manipulation ↗](https://arxiv.org/abs/2603.22435) arXiv (Cornell University) · no summary yet**Max Fu et al.*2026 · 7 citations*
22. **[NitroGen: An Open Foundation Model for Generalist Gaming Agents ↗](https://arxiv.org/abs/2601.02427) arXiv (Cornell University) · no summary yet**Loïc Magne et al.*2026 · 5 citations*
23. **[ENPIRE: Agentic Robot Policy Self-Improvement in the Real World ↗](https://arxiv.org/abs/2606.19980) arXiv (Cornell University) · no summary yet**Wenli Xiao et al.*2026 · 5 citations*
24. **[Self-Improving Vision-Language-Action Models with Data Generation via Residual RL ↗](https://arxiv.org/abs/2511.00091) arXiv (Cornell University) · no summary yet**Wenli Xiao et al.*2025 · 5 citations*
25. **[One-Step Diffusion Policy: Fast Visuomotor Policies via Diffusion Distillation ↗](https://arxiv.org/abs/2410.21257) arXiv (Cornell University) · no summary yet**Zhendong Wang et al.*2024 · 5 citations*

[See all 39 works by Linxi Fan →](https://md.research.elamur.ai/free/en/authors/linxi-fan/works/)

## Co-authors here

10 co-authors with a page, the most papers together first.

- [Anima Anandkumar](https://md.research.elamur.ai/free/en/authors/anima-anandkumar/) ×3
- [De-An Huang](https://md.research.elamur.ai/free/en/authors/de-an-huang/) ×3
- [Guanzhi Wang](https://md.research.elamur.ai/free/en/authors/guanzhi-wang/) ×2
- [Yuke Zhu](https://md.research.elamur.ai/free/en/authors/yuke-zhu/) ×2
- [Ekin Akyurek](https://md.research.elamur.ai/free/en/authors/ekin-akyurek/)
- [Igor Mordatch](https://md.research.elamur.ai/free/en/authors/igor-mordatch/)
- [Jacob Andreas](https://md.research.elamur.ai/free/en/authors/jacob-andreas/)
- [Shuang Li](https://md.research.elamur.ai/free/en/authors/shuang-li/)
- [Tao Chen](https://md.research.elamur.ai/free/en/authors/tao-chen/)
- [Yilun Du](https://md.research.elamur.ai/free/en/authors/yilun-du/)

## Venues

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

- Conference on Robot Learning
- Findings of the Association for Computational Linguistics: EMNLP 2023
- International Conference on Machine Learning
- Lecture notes in computer science

## Cited by

Papers of our library cite their works 1,447 times (of the 149,439 papers whose bibliographies we read); [216 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/linxi-fan/cited-by/).

Updated 2 November 2026