🧑‍🔬 Steven Zheng

🧭 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. Best Practices and Lessons Learned on Synthetic Data (2024 · 119 citations)
   Strong AI systems need large, varied and clean datasets, but such data is often scarce, expensive to label, or restricted by privacy rules.
2. In-Context Principle Learning from Mistakes (2024 · 19 citations)
   Standard in-context learning shows a model only correct demonstrations, so it never learns from what goes wrong on a task.

All works

3 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. Best Practices and Lessons Learned on Synthetic DataarXiv:2404.07503Ruibo Liu, Jerry Wei, Fangyu Liu, et al.2024 · 119 citations
2. In-Context Principle Learning from MistakesarXiv:2402.05403Tianjun Zhang, Aman Madaan, Luyu Gao, et al.2024 · 19 citations
3. Human-Level Competitive Pokémon via Scalable Offline Reinforcement Learning with Transformers ↗arXiv (Cornell University) · no summary yetJake Grigsby et al.2025 · 1 citation

🤝 Co-authors here

12 of 16 co-authors with a page, the most papers together first.

• Aman Madaan
• Andrew M. Dai
• Chenglei Si
• Daiyi Peng
• Denny Zhou
• Diyi Yang
• Fangyu Liu
• Jerry Wei
• Luyu Gao
• Niket Tandon
• Ruibo Liu
• Swaroop Mishra

🔗 Cited by

Papers of our library cite their works 3,191 times (of the 149,439 papers whose bibliographies we read); 651 citing papers with a page here →.

Updated 30 October 2026

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