--- title: "Guanzhi Wang — author profile and papers — Elamur Research" description: "Guanzhi Wang: 2 papers on Elamur Research (2022–2023), h-index 0 — affiliations, topics, co-authors and who cites them in our library." canonical: "https://research.elamur.ai/free/en/authors/guanzhi-wang/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/guanzhi-wang/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Guanzhi Wang # Guanzhi Wang Guanzhi Wang has 2 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/), [Linxi Fan](https://md.research.elamur.ai/free/en/authors/linxi-fan/). 2 papers in our library · 2022–2023 [OpenAlex](https://openalex.org/A5126405010) · [**h-index 0**](https://openalex.org/authors/A5126405010) · [3 works](https://openalex.org/works?filter=author.id:A5126405010) · [0 citations](https://openalex.org/works?filter=author.id:A5126405010&sort=cited_by_count:desc) OpenAlex, 2026-10-14 [📄 2 works in our library](https://md.research.elamur.ai/free/en/authors/guanzhi-wang/#papers) · [🔗 Cited 1,001 times in our library](https://md.research.elamur.ai/free/en/authors/guanzhi-wang/cited-by/) · [14 more in our library without a page yet](#also) · [⭐ Paper Stars ranking: #5618](https://md.research.elamur.ai/free/en/paper-stars/page/57/#star-5618) 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=Guanzhi+Wang) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Guanzhi+Wang) · [dblp](https://dblp.org/search?q=Guanzhi+Wang) · [ACL Anthology](https://aclanthology.org/search/?q=Guanzhi+Wang) ## Affiliations [🎓**California Institute of Technology** Pasadena · United States 2022–2026 · 11 papers](https://md.research.elamur.ai/free/en/universities/california-institute-of-technology/) · [🎓**Stanford University** Stanford · United States 2019–2021 · 4 papers](https://md.research.elamur.ai/free/en/universities/stanford-university/) · [🎓**Hong Kong University of Science and Technology** Hong Kong · China 2019–2021 · 2 papers](https://md.research.elamur.ai/free/en/universities/hong-kong-university-of-science-and-technology/) From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. ## 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 · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/) · [Computer Science · 2 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 · 1 work](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/guanzhi-wang/year/2023/) · [**2022** 1 paper](https://md.research.elamur.ai/free/en/authors/guanzhi-wang/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. ## All works 16 works of theirs in our library, the most cited first; 2 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. **[Open X-Embodiment: Robotic Learning Datasets and RT-X Models ↗](https://arxiv.org/abs/2310.08864) arXiv:2310.08864 · no summary yet**Embodiment Collaboration et al.*2023 · 204 citations* 3. [**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/) 4. [**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/) 5. **[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* 6. **[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* 7. **[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* 8. **[World Action Models are Zero-shot Policies ↗](https://arxiv.org/abs/2602.15922) arXiv (Cornell University) · no summary yet**Seonghyeon Ye et al.*2026 · 41 citations* 9. **[SECANT: Self-Expert Cloning for Zero-Shot Generalization of Visual Policies ↗](https://arxiv.org/abs/2106.09678) arXiv (Cornell University) · no summary yet**Fan, Linxi et al.*2021 · 16 citations* 10. **[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* 11. **[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* 12. **[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* 13. **[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* 14. **[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* 15. **[ASPIRE: Agentic /Skills Discovery for Robotics ↗](https://arxiv.org/abs/2607.00272) arXiv (Cornell University) · no summary yet**Runyu Lu et al.*2026 · 2 citations* 16. **[GaP: A Graph-as-Policy Multi-Agent Self-Learning Harness For Variational Automation Tasks ↗](https://arxiv.org/abs/2607.05369) arXiv (Cornell University) · no summary yet**Kaiyuan Chen et al.*2026 · 1 citation* ## Co-authors here 4 co-authors with a page, the most papers together first. - [Anima Anandkumar](https://md.research.elamur.ai/free/en/authors/anima-anandkumar/) ×2 - [De-An Huang](https://md.research.elamur.ai/free/en/authors/de-an-huang/) ×2 - [Linxi Fan](https://md.research.elamur.ai/free/en/authors/linxi-fan/) ×2 - [Yuke Zhu](https://md.research.elamur.ai/free/en/authors/yuke-zhu/) ×2 ## Venues Where their works here were published, the most works first, with the editions of those that have a page. - Lecture notes in computer science ## Cited by Papers of our library cite their works 1,001 times (of the 149,439 papers whose bibliographies we read); [140 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/guanzhi-wang/cited-by/). Updated 2 November 2026