A bottom-up method for developing a trait-based model of player behavior. - Mikhail A. Kabakov; Alessandro Canossa; Magy Seif El-Nasr; Jeremy B. Badler; Randy C. Colvin; Stefanie Tignor; Zhengxing Chen; Kunal Asarsa (CHI PLAY, 2014)

Games Research Today: Analyzing the Academic Landscape 2000-2014. - Edward F. Melcer; Truong-Huy D. Nguyen; Zhengxing Chen; Alessandro Canossa; Magy Seif El-Nasr; Katherine Isbister (FDG, 2015)

EOMM: An Engagement Optimized Matchmaking Framework. - Zhengxing Chen; Su Xue; John Kolen; Navid Aghdaie; Kazi A. Zaman; Yizhou Sun; Magy Seif El-Nasr (WWW, 2017)

Player Skill Decomposition in Multiplayer Online Battle Arenas. - Zhengxing Chen; Yizhou Sun; Magy Seif El-Nasr; Truong-Huy D. Nguyen (CoRR, 2017)

Q-DeckRec: A Fast Deck Recommendation System for Collectible Card Games. - Zhengxing Chen; Christopher Amato; Truong-Huy D. Nguyen; Seth Cooper; Yizhou Sun; Magy Seif El-Nasr (CIG, 2018)

The art of drafting: a team-oriented hero recommendation system for multiplayer online battle arena games. - Zhengxing Chen; Truong-Huy D. Nguyen; Yuyu Xu; Christopher Amato; Seth Cooper; Yizhou Sun; Magy Seif El-Nasr (RecSys, 2018)

Modeling Game Avatar Synergy and Opposition through Embedding in Multiplayer Online Battle Arena Games. - Zhengxing Chen; Yuyu Xu; Truong-Huy D. Nguyen; Yizhou Sun; Magy Seif El-Nasr (CoRR, 2018)

Band-limited Soft Actor Critic Model. - Miguel Campo; Zhengxing Chen; Luke Kung; Kittipat Virochsiri; Jianyu Wang (CoRR, 2020)

Using Vehicle Interior Noise Classification for Monitoring Urban Rail Transit Infrastructure. - Yifeng Wang; Ping Wang; Qihang Wang; Zhengxing Chen; Qing He (Sensors, 2020)

Reinforcement Learning-based Product Delivery Frequency Control. - Yang Liu; Zhengxing Chen; Kittipat Virochsiri; Juan Wang 019; Jiahao Wu 003; Feng Liang (AAAI, 2021)

A Feature Analysis Tool for Batch RL Datasets. - Ruiyang Xu; Zhengxing Chen (WWW (Companion Volume), 2021)

A Validation Tool for Designing Reinforcement Learning Environments. - Ruiyang Xu; Zhengxing Chen (CoRR, 2021)

Personalized Execution Time Optimization for the Scheduled Jobs. - Yang Liu; Juan Wang; Zhengxing Chen; Ian Fox; Imani Mufti; Jason Sukumaran; Baokun He; Xiling Sun; Feng Liang (CoRR, 2022)

CUFuse: Camera and Ultrasound Data Fusion for Rail Defect Detection. - Zhengxing Chen; Qihang Wang; Qing He 011; Tianle Yu; Min Zhang; Ping Wang 077 (IEEE Trans. Intell. Transp. Syst., 2022)

NASRec: Weight Sharing Neural Architecture Search for Recommender Systems. - Tunhou Zhang; Dehua Cheng; Yuchen He; Zhengxing Chen; Xiaoliang Dai; Liang Xiong; Feng Yan 001; Hai Li 001; Yiran Chen 001; Wei Wen (WWW, 2023)

Scaling User Modeling: Large-scale Online User Representations for Ads Personalization in Meta. - Wei Zhang; Dai Li; Chen Liang; Fang Zhou; Zhongke Zhang; Xuewei Wang; Ru Li; Yi Zhou; Yaning Huang; Dong Liang; Kai Wang; Zhangyuan Wang; et al. (CoRR, 2023)

Rankitect: Ranking Architecture Search Battling World-class Engineers at Meta Scale. - Wei Wen; Kuang-Hung Liu; Igor Fedorov; Xin Zhang 054; Hang Yin 005; Weiwei Chu; Kaveh Hassani; Mengying Sun; Jiang Liu 011; Xu Wang; Lin Jiang; Yuxin Chen 001; et al. (WWW (Companion Volume), 2024)

AutoML for Large Capacity Modeling of Meta's Ranking Systems. - Hang Yin 005; Kuang-Hung Liu; Mengying Sun; Yuxin Chen 001; Buyun Zhang; Jiang Liu 011; Vivek Sehgal; Rudresh Rajnikant Panchal; Eugen Hotaj; Xi Liu; Daifeng Guo; Jamey Zhang; et al. (WWW (Companion Volume), 2024)

Scaling User Modeling: Large-scale Online User Representations for Ads Personalization in Meta. - Wei Zhang; Dai Li; Chen Liang 001; Fang Zhou; Zhongke Zhang; Xuewei Wang; Ru Li; Yi Zhou; Yaning Huang; Dong Liang; Kai Wang; Zhangyuan Wang; et al. (WWW (Companion Volume), 2024)

Correction to: Learning to bid and rank together in recommendation systems. - Geng Ji 001; Wentao Jiang; Jiang Li; Fahmid Morshed Fahid; Zhengxing Chen; Yinghua Li; Jun Xiao; Chongxi Bao; Zheqing Zhu (Mach. Learn., 2024)

Learning to bid and rank together in recommendation systems. - Geng Ji 001; Wentao Jiang; Jiang Li; Fahmid Morshed Fahid; Zhengxing Chen; Yinghua Li; Jun Xiao; Chongxi Bao; Zheqing Zhu (Mach. Learn., 2024)

Law of the Weakest Link: Cross Capabilities of Large Language Models. - Ming Zhong 005; Aston Zhang; Xuewei Wang; Rui Hou; Wenhan Xiong; Chenguang Zhu 001; Zhengxing Chen; Liang Tan; Chloe Bi; Mike Lewis; Sravya Popuri; Sharan Narang; et al. (ICLR, 2025)

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)

Boosting LLM Reasoning via Spontaneous Self-Correction. - Xutong Zhao; Tengyu Xu; Xuewei Wang; Zhengxing Chen; Di Jin; Liang Tan; Yen-Ting; Zishun Yu; Zhuokai Zhao; Yun He; Sinong Wang; Han Fang; et al. (CoRR, 2025)

Towards Automated Model Design on Recommender Systems. - Tunhou Zhang; Dehua Cheng; Yuchen He; Zhengxing Chen; Xiaoliang Dai; Liang Xiong; Yudong Liu; Feng Cheng; Yufan Cao 002; Feng Yan 001; Hai Li 001; Yiran Chen 001; et al. (Trans. Recomm. Syst., 2025)