I am Teng Shi, a fourth-year Ph.D. student at the Gaoling School of Artificial Intelligence, Renmin University of China, advised by Professor Jun Xu and Professor Xiao Zhang.

My research interests include recommender systems, information retrieval, and large language models (LLMs), with a particular focus on generative recommendation and the joint modeling of search and recommendation. I am broadly interested in building intelligent systems that understand user intent and enable personalized, context-aware information access.

I welcome opportunities for collaboration or research internships. Feel free to contact me at shiteng@ruc.edu.cn.

Publications

(* denotes Equal Contribution)

Generative Recommendation

• GenSAR: Unifying Balanced Search and Recommendation with Generative Retrieval

  Teng Shi, Jun Xu, Xiao Zhang, Xiaoxue Zang, Kai Zheng, Yang Song, Enyun Yu | (RecSys 2025, CCF B) | Paper

• LLaDA-Rec: Discrete Diffusion for Parallel Semantic ID Generation in Generative Recommendation

  Teng Shi, Chenglei Shen, Weijie Yu, Shen Nie, Chongxuan Li, Xiao Zhang, Ming He, Yan Han, Jun Xu | (Arxiv) | Paper

• Think before recommend: Unleashing the latent reasoning power for sequential recommendation

  Jiakai Tang, Sunhao Dai, Teng Shi, Jun Xu, Xu Chen, Wen Chen, Wu Jian, Yuning Jiang | (Arxiv) | Paper

Joint Search and Recommendation

• UniSAR: Modeling User Transition Behaviors between Search and Recommendation

  Teng Shi, Zihua Si, Jun Xu, Xiao Zhang, Xiaoxue Zang, Kai Zheng, Dewei Leng, Yanan Niu, Yang Song | (SIGIR 2024, CCF A) | Paper

• Benefit from Rich: Tackling Search Interaction Sparsity in Search Enhanced Recommendation

  Teng Shi, Weijie Yu, Xiao Zhang, Ming He, Jianping Fan, Jun Xu | (CIKM 2025, CCF B) | Paper

• Similarity = Value? Consultation Value Assessment and Alignment for Personalized Search

  Weicong Qin, Yi Xu, Weijie Yu, Teng Shi, Chenglei Shen, Ming He, Jianping Fan, Xiao Zhang, Jun Xu | (EMNLP 2025, CCF B) | Paper

• Bridging Search and Recommendation through Latent Cross Reasoning

  Teng Shi, Weicong Qin, Weijie Yu, Xiao Zhang, Ming He, Jianping Fan, Jun Xu | (Arxiv) | Paper

Personalization of LLMs

• Retrieval Augmented Generation with Collaborative Filtering for Personalized Text Generation

  Teng Shi, Jun Xu, Xiao Zhang, Xiaoxue Zang, Kai Zheng, Yang Song, Han Li | (SIGIR 2025, CCF A) | Paper

• PrLM: Learning Explicit Reasoning for Personalized RAG via Contrastive Reward Optimization

  Kepu Zhang*, Teng Shi*, Weijie Yu, Jun Xu | (CIKM 2025, CCF B) | Paper

• Balancing Stylization and Truth via Disentangled Representation Steering

  Chenglei Shen, Zhongxiang Sun, Teng Shi, Xiao Zhang, Jun Xu | (Arxiv) | Paper

Recommender System

• Model-Agnostic Causal Embedding Learning for Counterfactually Group-Fair Recommendation

  Xiao Zhang*, Teng Shi*, Jun Xu, Zhenhua Dong, Jirong Wen (Co-first authors (student)) | (TKDE 2024, CCF A) | Paper

• SAQRec: Aligning Recommender Systems to User Satisfaction via Questionnaire Feedback

  Kepu Zhang, Teng Shi, Sunhao Dai, Xiao Zhang, Yinfeng Li, Jing Lu, Xiaoxue Zang, Yang Song, Jun Xu | (CIKM 2024, CCF B) | Paper

• Test-Time Alignment with State Space Model for Tracking User Interest Shifts in Sequential Recommendation

  Changshuo Zhang, Xiao Zhang, Teng Shi, Jun Xu, Jirong Wen | (RecSys 2025, CCF B) | Paper

• A survey of controllable learning: Methods and applications in information retrieval

  Chenglei Shen, Xiao Zhang, Teng Shi, Changshuo Zhang, Guofu Xie, Jun Xu | (FCS 2025, CCF B) | Paper

• QAGCF: Graph Collaborative Filtering for Q&A Recommendation

  Changshuo Zhang, Teng Shi, Xiao Zhang, Yanping Zheng, Ruobing Xie, Qi Liu, Jun Xu, Jirong Wen | (Arxiv) | Paper

• Modeling Domain and Feedback Transitions for Cross-Domain Sequential Recommendation

  Changshuo Zhang*, Teng Shi*, Xiao Zhang, Qi Liu, Ruobing Xie, Jun Xu, Jirong Wen | (Arxiv) | Paper

Educations

• 2022.09 - Present, PhD Candidate. Gaoling School of Artificial Intelligence, Renmin University of China.
• 2018.09 - 2022.06, Bachelor of Computer Science. School of Computer Science, Beijing Jiaotong University.

Internships

• 2025.04 - Present, Research Intern, Lenovo AI Lab
• 2023.08 - 2025.04, Research Intern, Kuaishou Technology
• 2022.03 - 2023.03, Research Intern, JD.com