I am 叶耀文 (Yaowen Ye), a first-year CS PhD student at UC Berkeley advised by Prof. Jacob Steinhardt and Prof. Stuart Russell. This summer I'm working at Transluce as a research intern.
I work on understanding the limitations of human oversight of AI systems and developing scalable approaches to address them. Recently, I've been thinking about:
- What emergent risks will arise when many agents are deployed in shared environments? Can existing oversight methods scale to address them?
- Can we predict which generalizations will emerge during LLM training, especially surprising or problematic ones? How can automated analysis of training data and model internals help?
- LLM chatbots operate in an unusual environment: their human users. How can we design incentives that discourage manipulating this environment for higher reward?
- How to make RL with imperfect reward functions robust? How to prevent reward hacking?
Ultimately, I aim to ensure that humans can maintain meaningful oversight of AI systems as they scale, thereby keeping them safe.
Feel free to reach out if you're interested in my research! I also enjoy mentoring, so if you are an undergrad and think my advice might be helpful, I'd be happy to connect.
Before joining Berkeley, I did my undergrad at The University of Hong Kong. During my undergrad, I also worked on cognitive reasoning, intuitive physics, learning on graphs, and recommender systems. I was fortunate to be advised by
Prof. Yixin Zhu at
PKU Cognitive Reasoning Lab and
Prof. Chao Huang at
HKU Data Intelligence Lab.
Links:
[X] [Scholar] [Email] [Give me feedback!]
Publications
2026
Norm Enforcement for AI Agents: Robustly Shaping Behavior in Multi-Agent Systems
Workshop on Trustworthy AI for Good @ ICML2026. Oral. Best paper award (CoopAI track).
Annual Conference on Neural Information Processing Systems (NeurIPS), 2026. Spotlight.
Yaowen Ye, Jacob Steinhardt.
[paper]
On-Policy Counterfactual Influence
Annual Conference on Neural Information Processing Systems (NeurIPS), 2026.
Rhys Gould, Yaowen Ye, Stuart Russell, Jacob Steinhardt.
2025
Auditing Black-Box LLM APIs with a Rank-Based Uniformity Test
International Conference on Learning Representations (ICLR), 2026.
Xiaoyuan Zhu, Yaowen Ye*, Tianyi Qiu*, Hanlin Zhu†, Sijun Tan†, Ajraf Mannan, Jonathan Michala, Raluca Ada Popa, Willie Neiswanger.
[paper]
Iterative Label Refinement Matters More than Preference Optimization under Weak Supervision.
International Conference on Learning Representations (ICLR), 2025. Spotlight.
Yaowen Ye*, Cassidy Laidlaw* and Jacob Steinhardt.
[paper]
2023
Graph Masked Autoencoder for Sequential Recommendation.
ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), 2023.
Yaowen Ye, Chao Huang and Lianghao Xia.
[paper]
Masked Graph Transformer for Recommendation.
ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), 2023.
Chaoliu Li, Chao Huang, Lianghao Xia, Xubin Ren, Yaowen Ye and Yong Xu.
[paper]
Friend Links
Names are listed here because of an old mysterious tradition. Many names do not appear on this list but are still my friends :)
(almost alphabetical order)