| 2026 | WWW | PMIScore: An Unsupervised Approach to Quantify Dialogue Engagement. | Yongkang Guo, Zhihuan Huang, Yuqing Kong |
| 2025 | ICLR | Benchmarking LLMs' Judgments with No Gold Standard. | Shengwei Xu, Yuxuan Lu, Grant Schoenebeck, Yuqing Kong |
| 2025 | WWW | Learning against Non-credible Second-Price Auctions. | Qian Wang, Xuanzhi Xia, Zongjun Yang, Xiaotie Deng, Yuqing Kong, Zhilin Zhang, Liang Wang, Chuan Yu, Jian Xu, Bo Zheng |
| 2025 | WWW | Robust Aggregation with Adversarial Experts. | Yongkang Guo, Yuqing Kong |
| 2025 | WWW | Mitigating the Participation Bias by Balancing Extreme Ratings. | Yongkang Guo, Yuqing Kong, Jialiang Liu |
| 2024 | WWW | Robust Decision Aggregation with Second-order Information. | Yuqi Pan, Zhaohua Chen, Yuqing Kong |
| 2023 | ICML | Learning to Bid in Repeated First-Price Auctions with Budgets. | Qian Wang, Zongjun Yang, Xiaotie Deng, Yuqing Kong |
| 2023 | WWW | Near-Optimal Experimental Design Under the Budget Constraint in Online Platforms. | Yongkang Guo, Yuan Yuan, Jinshan Zhang, Yuqing Kong, Zhihua Zhu, Zheng Cai |
| 2022 | WWW | BONUS! Maximizing Surprise. | Zhihuan Huang, Yuqing Kong, Tracy Xiao Liu, Grant Schoenebeck, Shengwei Xu |
| 2021 | IJCAI | SURPRISE! and When to Schedule It. | Zhihuan Huang, Shengwei Xu, You Shan, Yuxuan Lu, Yuqing Kong, Tracy Xiao Liu, Grant Schoenebeck |
| 2020 | AAAI | Information Elicitation Mechanisms for Statistical Estimation. | Yuqing Kong, Grant Schoenebeck, Biaoshuai Tao, Fang-Yi Yu |
| 2020 | ECCV | TCGM: An Information-Theoretic Framework for Semi-supervised Multi-modality Learning. | Xinwei Sun, Yilun Xu, Peng Cao, Yuqing Kong, Lingjing Hu, Shanghang Zhang, Yizhou Wang |
| 2020 | SODA | Dominantly Truthful Multi-task Peer Prediction with a Constant Number of Tasks. | Yuqing Kong |
| 2019 | AAAI | f-Similarity Preservation Loss for Soft Labels: A Demonstration on Cross-Corpus Speech Emotion Recognition. | Biqiao Zhang, Yuqing Kong, Georg Essl, Emily Mower Provost |
| 2019 | ICLR | Max-MIG: an Information Theoretic Approach for Joint Learning from Crowds. | Peng Cao, Yilun Xu, Yuqing Kong, Yizhou Wang |