| 2026 | AAAI | From Mathematical Reasoning to Code: Generalization of Process Reward Models in Test-Time Scaling. | Zhengyu Chen, Yudong Wang, Teng Xiao, Ruochen Zhou, Xuesheng Yang, Wei Wang, Zhifang Sui, Jingang Wang |
| 2026 | AAAI | Scaling and Transferability of Annealing Strategies in Large Language Model Training. | Siqi Wang, Zhengyu Chen, Teng Xiao, Zheqi Lv, Jinluan Yang, Xunliang Cai, Jingang Wang, Xiaomeng Li |
| 2026 | ACL | From AR to Diffusion: Efficiently Adapting Large Language Models with Strictly Causal and Elastic Horizons. | Xiangyu Ma, Teng Xiao, Zuchao Li, Lefei Zhang |
| 2026 | EACL | Incentivizing Strong Reasoning from Weak Supervision. | Yige Yuan, Teng Xiao, Shuchang Tao, Xue Wang, Jinyang Gao, Bolin Ding, Bingbing Xu |
| 2025 | ACL | Revisiting Scaling Laws for Language Models: The Role of Data Quality and Training Strategies. | Zhengyu Chen, Siqi Wang, Teng Xiao, Yudong Wang, Shiqi Chen, Xunliang Cai, Junxian He, Jingang Wang |
| 2025 | ACL | Dialogue-RAG: Enhancing Retrieval for LLMs via Node-Linking Utterance Rewriting. | Qiwei Li, Teng Xiao, Zuchao Li, Ping Wang, Mengjia Shen, Hai Zhao |
| 2025 | CIKM | The 1st Workshop on LLM Agents for Social Simulation. | Yige Yuan, Junkai Zhou, Bingbing Xu, Liang Pang, Du Su, An Zhang, Teng Xiao, Fengli Xu, Zhaochun Ren, Xu Chen |
| 2025 | EMNLP | Reinforcement Learning for Large Language Models via Group Preference Reward Shaping. | Huaisheng Zhu, Siyuan Xu, Hangfan Zhang, Teng Xiao, Zhimeng Guo, Shijie Zhou, Shuyue Hu, Vasant G. Honavar |
| 2025 | ICLR | SimPER: A Minimalist Approach to Preference Alignment without Hyperparameters. | Teng Xiao, Yige Yuan, Zhengyu Chen, Mingxiao Li, Shangsong Liang, Zhaochun Ren, Vasant G. Honavar |
| 2025 | ICLR | On a Connection Between Imitation Learning and RLHF. | Teng Xiao, Yige Yuan, Mingxiao Li, Zhengyu Chen, Vasant G. Honavar |
| 2025 | ICLR | DSPO: Direct Score Preference Optimization for Diffusion Model Alignment. | Huaisheng Zhu, Teng Xiao, Vasant G. Honavar |
| 2025 | NAACL | InfoPO: On Mutual Information Maximization for Large Language Model Alignment. | Teng Xiao, Zhen Ge, Sujay Sanghavi, Tian Wang, Julian Katz-Samuels, Marc Versage, Qingjun Cui, Trishul Chilimbi |
| 2025 | WWW | Leveraging Invariant Principle for Heterophilic Graph Structure Distribution Shifts. | Jinluan Yang, Zhengyu Chen, Teng Xiao, Yong Lin, Wenqiao Zhang, Kun Kuang |
| 2025 | SIGIR | Fact-Level Calibration and Correction for Long-Form Generations. | Yige Yuan, Bingbing Xu, Hexiang Tan, Fei Sun, Teng Xiao, Wei Li, Huawei Shen, Xueqi Cheng |
| 2024 | AAAI | Learning to Reweight for Generalizable Graph Neural Network. | Zhengyu Chen, Teng Xiao, Kun Kuang, Zheqi Lv, Min Zhang, Jinluan Yang, Chengqiang Lu, Hongxia Yang, Fei Wu |
| 2024 | EMNLP | How to Leverage Demonstration Data in Alignment for Large Language Model? A Self-Imitation Learning Perspective. | Teng Xiao, Mingxiao Li, Yige Yuan, Huaisheng Zhu, Chao Cui, Vasant G. Honavar |
| 2024 | ICASSP | Pareto Graph Self-Supervised Learning. | Zhengyu Chen, Teng Xiao, Donglin Wang, Min Zhang |
| 2024 | ICML | In-Context Sharpness as Alerts: An Inner Representation Perspective for Hallucination Mitigation. | Shiqi Chen, Miao Xiong, Junteng Liu, Zhengxuan Wu, Teng Xiao, Siyang Gao, Junxian He |
| 2024 | ICML | Efficient Contrastive Learning for Fast and Accurate Inference on Graphs. | Teng Xiao, Huaisheng Zhu, Zhiwei Zhang, Zhimeng Guo, Charu C. Aggarwal, Suhang Wang, Vasant G. Honavar |
| 2023 | CIKM | Towards Fair Graph Neural Networks via Graph Counterfactual. | Zhimeng Guo, Jialiang Li, Teng Xiao, Yao Ma, Suhang Wang |
| 2023 | KDD | Reconsidering Learning Objectives in Unbiased Recommendation: A Distribution Shift Perspective. | Teng Xiao, Zhengyu Chen, Suhang Wang |
| 2022 | AAAI | Towards Off-Policy Learning for Ranking Policies with Logged Feedback. | Teng Xiao, Suhang Wang |
| 2022 | CIKM | Representation Matters When Learning From Biased Feedback in Recommendation. | Teng Xiao, Zhengyu Chen, Suhang Wang |
| 2022 | ICDE | BA-GNN: On Learning Bias-Aware Graph Neural Network. | Zhengyu Chen, Teng Xiao, Kun Kuang |
| 2022 | WSDM | Towards Unbiased and Robust Causal Ranking for Recommender Systems. | Teng Xiao, Suhang Wang |
| 2021 | AAAI | A General Offline Reinforcement Learning Framework for Interactive Recommendation. | Teng Xiao, Donglin Wang |
| 2021 | KDD | Learning How to Propagate Messages in Graph Neural Networks. | Teng Xiao, Zhengyu Chen, Donglin Wang, Suhang Wang |
| 2019 | AAAI | Bayesian Deep Collaborative Matrix Factorization. | Teng Xiao, Shangsong Liang, Weizhou Shen, Zaiqiao Meng |
| 2019 | CIKM | Dynamic Collaborative Recurrent Learning. | Teng Xiao, Shangsong Liang, Zaiqiao Meng |
| 2019 | CIKM | Dynamic Bayesian Metric Learning for Personalized Product Search. | Teng Xiao, Jiaxin Ren, Zaiqiao Meng, Huan Sun, Shangsong Liang |
| 2019 | CVPR | Robustifying Relative Orientations With Respect to Repetitive Structures and Very Short Baselines for Global SfM. | Xin Wang, Teng Xiao, Michael Gruber, Christian Heipke |
| 2019 | IJCAI | ISLF: Interest Shift and Latent Factors Combination Model for Session-based Recommendation. | Jing Song, Hong Shen, Zijing Ou, Junyi Zhang, Teng Xiao, Shangsong Liang |
| 2019 | PAKDD | Neural Variational Matrix Factorization with Side Information for Collaborative Filtering. | Teng Xiao, Hong Shen |
| 2019 | PAKDD | Variational Deep Collaborative Matrix Factorization for Social Recommendation. | Teng Xiao, Hui Tian, Hong Shen |
| 2019 | WWW | Hierarchical Neural Variational Model for Personalized Sequential Recommendation. | Teng Xiao, Shangsong Liang, Zaiqiao Meng |