Security games with contagion: handling asymmetric information. - Jason Tsai; Yundi Qian; Yevgeniy Vorobeychik; Christopher Kiekintveld; Milind Tambe (AAMAS, 2013)

A fast table lookup based, statistical model driven non-uniform unit selection TTS. - Yao Qian; Frank K. Soong; Xiaobo Zhou; Yundi Qian; Xiaotian Zhang (ICASSP, 2013)

Defender (Mis)coordination in Security Games. - Albert Xin Jiang; Ariel D. Procaccia; Yundi Qian; Nisarg Shah 001; Milind Tambe (IJCAI, 2013)

Bayesian Security Games for Controlling Contagion. - Jason Tsai; Yundi Qian; Yevgeniy Vorobeychik; Christopher Kiekintveld; Milind Tambe (SocialCom, 2013)

Planning and learning in security games. - Francesco Maria Delle Fave; Yundi Qian; Albert Xin Jiang; Matthew Brown 002; Milind Tambe (SIGecom Exch., 2013)

Online planning for optimal protector strategies in resource conservation games. - Yundi Qian; William B. Haskell 001; Albert Xin Jiang; Milind Tambe (AAMAS, 2014)

To Handle, to Learn and to Manipulate the Attacker's (Uncertain) Payoffs in Security Games: Doctoral Consortium. - Yundi Qian (AAMAS, 2015)

Robust Strategy against Unknown Risk-averse Attackers in Security Games. - Yundi Qian; William B. Haskell 001; Milind Tambe (AAMAS, 2015)

Restless Poachers: Handling Exploration-Exploitation Tradeoffs in Security Domains. - Yundi Qian; Chao Zhang 049; Bhaskar Krishnamachari; Milind Tambe (AAMAS, 2016)

Using Abstractions to Solve Opportunistic Crime Security Games at Scale. - Chao Zhang 049; Victor Bucarey; Ayan Mukhopadhyay; Arunesh Sinha; Yundi Qian; Yevgeniy Vorobeychik; Milind Tambe (AAMAS, 2016)

MLGO: a Machine Learning Guided Compiler Optimizations Framework. - Mircea Trofin; Yundi Qian; Eugene Brevdo; Zinan Lin 001; Krzysztof Choromanski; David Li (CoRR, 2021)

Frontier Language Models are not Robust to Adversarial Arithmetic, or "What do I need to say so you agree 2+2=5? - C. Daniel Freeman; Laura Culp; Aaron Parisi; Maxwell L. Bileschi; Gamaleldin F. Elsayed; Alex Rizkowsky; Isabelle Simpson; Alex Alemi; Azade Nova; Ben Adlam; Bernd Bohnet; Gaurav Mishra; et al. (CoRR, 2023)

Beyond Human Data: Scaling Self-Training for Problem-Solving with Language Models. - Avi Singh; John D. Co-Reyes; Rishabh Agarwal; Ankesh Anand; Piyush Patil; Xavier Garcia; Peter J. Liu; James Harrison; Jaehoon Lee 001; Kelvin Xu; Aaron T. Parisi; Abhishek Kumar; et al. (Trans. Mach. Learn. Res., 2024)

Self-Generated Critiques Boost Reward Modeling for Language Models. - Yue Yu; Zhengxing Chen; Aston Zhang; Liang Tan; Chenguang Zhu 001; Richard Yuanzhe Pang; Yundi Qian; Xuewei Wang; Suchin Gururangan; Chao Zhang; Melanie Kambadur; Dhruv Mahajan 001; et al. (NAACL (Long Papers), 2025)

LlamaRL: A Distributed Asynchronous Reinforcement Learning Framework for Efficient Large-scale LLM Training. - Bo Wu; Sid Wang; Yunhao Tang; Jia Ding; Eryk Helenowski; Liang Tan; Tengyu Xu; Tushar Gowda; Zhengxing Chen; Chen Zhu; Xiaocheng Tang; Yundi Qian; et al. (CoRR, 2025)