AI Engine Lab

Coding the Next Wave of Intelligence

Introduction

AI Engine Lab is a research team at Gaoling School of Artificial Intelligence, Renmin University of China. Our team is driven by a passion for technological advancement and innovation.

We hope that through our efforts, we can provide more in-depth, equitable and reliable methods and strategies for artificial intelligence. Our research directions include large language models, causal inference and recommender systems.

Openings: we are always looking for highly self-motivated students to work with us as PhD, master or visiting students. Please email us at xu.chen@ruc.edu.cn if you are interested in our team.

Recent Publications

2026

OneRank: Unified Transformer-Native Ranking Architecture for Multi-Task Recommendation

Jiakai Tang, Sunhao Dai, Kun Wang, Zhiluohan Guo, Yu Zhao, Cong Fu, Kangle Wu, Yabo Ni, Anxiang Zeng, Xu Chen, Jun Xu

ACM SIGKDD Conference on Knowledge Discovery and Data Mining Applied Data Science Track (KDD ADS)

Interactive Recommendation Agent with Active User Commands

Jiakai Tang, Wen Chen, Yujie Luo, XunkeXi, YI CHAO, Dian Chen, Zhujin Gao, Yang Li, Fei Sun, Xueyang Feng, Sunhao Dai, Xu Chen, Jian Wu, Yuning Jiang, Bo Zheng

ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD)

Think Before Recommend: Unleashing the Latent Reasoning Power for Sequential Recommendation

Jiakai Tang, Sunhao Dai, Teng Shi, Jun Xu, Xu Chen, Wen Chen, Jian Wu, Yuning Jiang

IEEE Transactions on Knowledge and Data Engineering (TKDE)

From Coarse to Fine: Self-Adaptive Hierarchical Planning for LLM Agents

Haoran Tan, Zeyu Zhang, Chen Ma, Tianze Liu, Quanyu Dai, Xu Chen

Annual Meeting of the Association for Computational Linguistics (ACL-findings)

Learning from Cognition: Enhancing RL Efficiency for LLM Reasoning via Hierarchical Metacognitive Decomposition and Refinement

Zexu Sun, Yongcheng Zeng, Erxue Min, Heyang Gao, Bokai Ji, Dugang Liu, Xing Tang, Xiuqiang He, Xu Chen

Annual Meeting of the Association for Computational Linguistics (ACL)

Divergence Meets Consensus: A Multi-Source Negative Sampling Framework for Sequential Recommendation

Yuanzi Li, Lingjie Wang, Jingyu Zhao, Zihang Tian, Yuhan Wang, Lei Wang, Xu Chen

International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR)

Solving the Granularity Mismatch: Hierarchical Preference Learning for Long-Horizon LLM Agents

Heyang Gao, Zexu Sun, Erxue Min, Hengyi Cai, Shuaiqiang Wang, Dawei Yin, Xu Chen

International Conference on Learning Representations (ICLR)

Prompt and Parameter Co-Optimization for Large Language Models

Xiaohe Bo, Rui Li, Zexu Sun, Quanyu Dai, Zeyu Zhang, Zihang Tian, Xu Chen, Zhenhua Dong

International Conference on Learning Representations (ICLR)

VeriRole: Verifiable Role-Awareness through Hint-Guided Reinforcement Learning

Zongsheng Wang, Kaili Sun, Bowen Wu, Qun Yu, Ying Li, Xu Chen, Baoxun Wang

International Conference on Learning Representations (ICLR)

CurES: From Gradient Analysis to Efficient Curriculum Learning for Reasoning LLMs

Yongcheng Zeng, Zexu Sun, Bokai Ji, Erxue Min, Hengyi Cai, Shuaiqiang Wang, Dawei Yin, Haifeng Zhang, Xu Chen, Jun Wang

International Conference on Learning Representations (ICLR)

Optimizing Multi-Turn Interactive Recommendation Agents via Generative Intrinsic Motivation

Xueyang Feng, Jiakai Tang, Xu Chen, Quanyu Dai, Zhenhua Dong

The Web Conference (WWW)

Explicit v.s. Implicit Memory: Exploring Multi-hop Complex Reasoning Over Personalized Information

Zeyu Zhang, Yang Zhang, Haoran Tan, Rui Li, Xu Chen

ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD)