Yekun Chai

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My research centers on pre-training for foundation models — what to train on, at what scale, and how those early choices set the ceiling on reasoning, code, and agentic behavior later. I am particularly interested in the pre-training ↔ post-training interface, and in understanding it in a principled way rather than through trial and error.

I have contributed to ERNIE, ERNIE-Code, and StarCoder 2.

News

Aug 21, 2025 Four papers accepted to EMNLP 2025.
May 16, 2025 Curiosity-driven RLHF accepted to ACL 2025. [code]
Jan 23, 2025 MA-RLHF accepted to ICLR 2025. [paper] [code]

Latest Posts

Selected Publications

  1. MA-RLHF: Reinforcement Learning from Human Feedback with Macro Actions
    Yekun Chai*†Haoran Sun*^Huang FangShuohuan Wang, and 2 more authors
    In The Thirteenth International Conference on Learning Representations, 2025
  2. ICLR Spotlight
    Tool-Augmented Reward Modeling
    Lei Li*^Yekun Chai*†Shuohuan WangYu Sun, and 3 more authors
    In The Twelfth International Conference on Learning Representations(top 5%) , 2024
  3. ERNIE-Code: Beyond English-Centric Cross-lingual Pretraining for Programming Languages
    Yekun ChaiShuohuan Wang, Chao Pang, Yu Sun, and 2 more authors
    In Findings of the Association for Computational Linguistics: ACL 2023, Jul 2023