🧑‍🔬 Yunzhu Li

🏛️ Affiliations

🎓Columbia UniversityNew York · United States2024–2026 · 37 paperscurrent🎓Massachusetts Institute of TechnologyCambridge · United States2017–2022 · 20 papers🎓Stanford UniversityStanford · United States2017–2024 · 13 papers🎓University of Illinois Urbana-ChampaignUrbana · United States2023–2025 · 11 papers🔬MIT Computer Science and Artificial Intelligence LaboratoryCambridge · United States2018–2021 · 8 papers🎓Peking UniversityBeijing · China2016–2025 · 4 papers🎓University of PennsylvaniaPhiladelphia · United States2023–2024 · 2 papers🎓University of California San DiegoSan Diego · United States2022 · 2 papers

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.

📅 Works by year

2020s

📄 Papers

The most cited first (OpenAlex and our library).

1. Executable Code Actions Elicit Better LLM Agents (2024 · 165 citations)
   LLM agents usually express their actions as JSON objects or as text in a fixed template. This ties them to a predefined set of tools and makes it hard to chain or combine several tools in one step. The authors propose CodeAct, where the agent writes executable Python as its action. A Python interpreter runs the code…
2. Current Agents Fail to Leverage World Model as Tool for Foresight (2026 · 1 citation)
   The paper asks whether today's vision-language agents can treat a generative world model as an optional external tool: a simulator they consult to preview the consequences of an action before committing to it in the real environment.

All works

5 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. Open X-Embodiment: Robotic Learning Datasets and RT-X Models ↗arXiv:2310.08864 · no summary yetEmbodiment Collaboration et al.2023 · 204 citations
2. Executable Code Actions Elicit Better LLM AgentsarXiv:2402.01030Xingyao Wang, Yangyi Chen, Lifan Yuan, et al.2024 · 165 citations
3. InfoGAIL: Interpretable Imitation Learning from Visual Demonstrations ↗arXiv (Cornell University) · no summary yetYunzhu Li, Jiaming Song, Stefano Ermon2017 · 142 citations
4. Current Agents Fail to Leverage World Model as Tool for ForesightAnnual Meeting of the Association for Computational Linguistics (ACL)Cheng Qian, Emre Can Acikgoz, Bingxuan Li, et al.2026 · 1 citation
5. ManipulationNet: An Infrastructure for Benchmarking Real-World Robot Manipulation with Physical Skill Challenges and Embodied Multimodal Reasoning ↗arXiv (Cornell University) · no summary yetYiting Chen et al.2026

🤝 Co-authors here

12 of 14 co-authors with a page, the most papers together first.

• Heng Ji ×2
• Bingxiang He
• Bingxuan Li
• Cheng Qian
• Dilek Hakkani-Tür
• Emre Can Acikgoz
• Gokhan Tur
• Hao Peng
• Lifan Yuan
• Qinyu Luo
• Xingyao Wang
• Xiusi Chen

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): ACL 2026

🔗 Cited by

Papers of our library cite their works 270 times (of the 149,439 papers whose bibliographies we read); 43 citing papers with a page here →.

Updated 31 October 2026

↑ back to top

This page in Markdown → https://md.research.elamur.ai/free/en/authors/yunzhu-li/