Mingyue Cheng
Mingyue Cheng  程明月
Ph.D  ·  Associate Researcher
State Key Laboratory of Cognitive Intelligence
School of Computer Science and Technology,  University of Science and Technology of China
Google Scholar DBLP GitHub USTC-AGI Group
Email: mycheng@ustc.edu.cn
Address: B709, Xinzhi Building, Gaoxin Campus of USTC, Hefei, Anhui, China, 230031

Biography

I am an Associate Researcher at the School of Computer Science and Technology, USTC. I am also affiliated with the State Key Laboratory of Cognitive Intelligence at the side of USTC, working under the leadership of Prof. Enhong Chen and Prof. Qi Liu. Previously, I obtained my Ph.D. degree under the supervision of Prof. Qi Liu.

Research Interests

My research focuses on structured data analysis and LLM-based reasoning & agents, with applications in AI for Science and Recommender Systems.

欢迎脚踏实地而又积极主动的本科生、研究生同学加入认知智能全国重点实验室 USTC-AGI 研究组。

Latest News

Selected Publications

(* Corresponding Author, + Equal Contribution)

📘 Preprint

  1. Mingyue Cheng, Xiaoyu Tao, Qi Liu, Ze Guo, Enhong Chen, Position: Beyond Model-Centric Prediction — Agentic Time Series Forecasting. Highlight: 率先探索 Agentic Time Series Forecasting 范式的立场 paper。 (Preprint) [PDF]
  2. Xiaohan Zhang, Tian Gao, Mingyue Cheng*, Bokai Pan, Ze Guo, Yaguo Liu, Xiaoyu Tao, AlphaCast: A Human Wisdom-LLM Intelligence Co-Reasoning Framework for Interactive Time Series Forecasting. Highlight: 率先探索人机协同交互式时间序列预测范式。 (Preprint) [PDF] [Code]
  3. Xiaoyu Tao, Mingyue Cheng, Chuang Jiang, Tian Gao, Huanjian Zhang, Yaguo Liu, Cast-R1: Learning Tool-Augmented Sequential Decision Policies for Time Series Forecasting. Highlight: 首个基于多轮强化学习训练的时间序列预测智能体。 (Preprint) [PDF] [Code]
  4. Xiaoyu Tao, Mingyue Cheng*, Ze Guo, Shuo Yu, Yaguo Liu, Qi Liu, Shijin Wang, MemCast: Memory-Driven Time Series Forecasting with Experience-Conditioned Reasoning. Highlight: 率先探索基于经验积累与持续进化的时间序列预测范式。 (Preprint) [PDF]
  5. Yitong Zhou, Yucong Luo, Mingyue Cheng*, Jiahao Wang, Daoyu Wang, Tingyue Pan, Jintao Zhang, Qi Liu, Enhong Chen, Time Series Forecasting as Reasoning: A Slow-Thinking Approach with Reinforced LLMs. (Preprint) [PDF] [Code]
  6. Xiaoyu Tao, Yuchong Wu, Mingyue Cheng, Ze Guo, Tian Gao, AnomaMind: Agentic Time Series Anomaly Detection with Tool-Augmented Reasoning. (Preprint) [PDF]

📘 Released Survey

  1. Mingyue Cheng, Zhiding Liu, Xiaoyu Tao, Qi Liu*, Jintao Zhang, Tingyue Pan, Shilong Zhang, Panjing He, Xiaohan Zhang, Daoyu Wang, Jiahao Wang, Enhong Chen, A Comprehensive Survey of Time Series Forecasting: Concepts, Challenges, and Future Directions. (Preprint) [PDF] [Code]
  2. Mingyue Cheng, Qingyang Mao, Qi Liu*, Yitong Zhou, Yupeng Li, Jiahao Wang, Jiaying Lin, Jiawei Cao, Enhong Chen, A Survey on Table Mining with Large Language Models: Challenges, Advancements and Prospects. (Preprint) [PDF] [Code]
  3. Mingyue Cheng, Yucong Luo, Jie Ouyang, Qi Liu*, et al., A Survey on Knowledge-Oriented Retrieval-Augmented Generation. (Preprint) [PDF] [Code]

🐎 Year of the Fire Horse (Bing Wu Year, 2026)

  1. Huajian Zhang, Mingyue Cheng*, Yucong Luo, Xiaoyu Tao, STaR: Towards Cognitive Table Reasoning via Slow-Thinking Large Language Models. (ACM WWW2026) [PDF] [Code]
  2. Zhiding Liu, Ben Chen, Mingyue Cheng*, Enhong Chen, Li Li, Chenyi Lei, Wenwu Ou, Han Li and Kun Gai, Towards Context-aware Reasoning-enhanced Generative Searching in E-commerce. (ACM WWW2026) [PDF]
  3. Shuo Yu, Mingyue Cheng*, Daoyu Wang, Qi Liu, Zirui Liu, Ze Guo, Xiaoyu Tao, MemWeaver: A Hierarchical Memory from Textual Interactive Behaviors for Personalized Generation. (ACM WWW2026) [PDF]
  4. Qingchuan Li, Jiatong Li, Zirui Liu, Mingyue Cheng, Yitong Zhou, Yuting Zeng, Qi Liu and Tongxuan Liu, Are LLMs Stable Formal Logic Translators in Logical Reasoning Across Linguistically Diversified Texts? (ACM WWW2026)
  5. Li Li, Mingyue Cheng*, Yuyang Ye, Zhiding Liu, Enhong Chen, Preference Trajectory Modeling via Flow Matching for Sequential Recommendation. (DASFAA2026)
  6. Zirui Liu, Xianquan Wang, Yan Zhuang, Jiatong Li, Qi Liu, Shuanghong Shen, Mingyue Cheng, Shijin Wang, Fewer Battles, More Gain: An Information-Efficient Framework for Arena-based LLM Evaluation. (ICLR2026) [PDF]
  7. Qingyang Mao, Qi Cai, Yehao Li, Yingwei Pan, Mingyue Cheng, Ting Yao, Qi Liu, Tao Mei, Visual Autoregressive Modeling for Instruction-Guided Image Editing. (ICLR2026)
  8. Mingyue Cheng, Jiahao Wang, Daoyu Wang, Xiaoyu Tao, Qi Liu*, Enhong Chen, Can Slow-Thinking LLMs Reason Over Time? Empirical Studies in Time Series Forecasting. Highlight: 首次提出基于慢思考思维链推理的时序预测范式。 ACM WSDM2026: 99–110, Feb 2026. [PDF] [Code]
  9. Mingyue Cheng, Xiaoyu Tao, Zhiding Liu, Qi Liu*, Hao Zhang, Rujiao Zhang and Enhong Chen, TimeMAE: Self-Supervised Representations of Time Series with Decoupled Masked Autoencoders, ACM WSDM2026: 498–508, Feb 2026. [PDF] [Code]
  10. Chuang Jiang, Mingyue Cheng*, Xiaoyu Tao, Qingyang Mao, Jie Ouyang and Qi Liu, TableMind: An Autonomous Programmatic Agent for Tool-Augmented Table Reasoning. Highlight: 率先探索基于多轮强化学习的智能体式表格推理范式。 ACM WSDM2026: 260–270, Feb 2026. [PDF] [Code]
  11. Qingchuan Li, Mingyue Cheng*, Zirui Liu, Daoyu Wang, Yuting Zeng, Tongxuan Liu, From Hypothesis to Premises: LLM-based Backward Logical Reasoning with Selective Symbolic Translation. (AAAI2026)
  12. Yupeng Li, Mingyue Cheng*, Yucong Luo, Yitong Zhou, Qingyang Mao, Shijin Wang, BLADE: A Behavior-Level Data Augmentation Framework with Dual Fusion Modeling for Multi-Behavior Sequential Recommendation. (AAAI2026)
  13. Xian Guo, Ben Chen, Siyuan Wang, YingYang, Mingyue Cheng, Chenyi Lei, Yuqing Ding, Han Li, OneSug: The Unified End-to-End Generative Framework for E-commerce Query Suggestion. (AAAI2026)

🐍 Year of the Wood Snake (Yi Si Year, 2025)

  1. Mingyue Cheng, Jiqian Yang, Tingyue Pan, Qi Liu*, Zhi Li, ConvTimeNet: A Deep Hierarchical Fully Convolutional Model for Multivariate Time Series Analysis, ACM WWW2025, Sydney, 2025. [PDF] [Code] — Included in sktime
  2. Xiaoyu Tao, Tingyue Pan, Mingyue Cheng*, Yucong Luo, Qi Liu, Enhong Chen, Hierarchical Multimodal LLMs with Semantic Space Alignment for Enhanced Time Series Classification. (ACM TIST) [PDF] [Code]
  3. Mingyue Cheng, Yiheng Chen, Qi Liu*, Zhiding Liu, Yucong Luo, Enhong Chen, InstrucTime: Advancing Time Series Classification with Multimodal Language Modeling, ACM WSDM2025 (Best of WSDM): 792–800, Hannover, 2025. [PDF] [Code] [Poster]
  4. Mingyue Cheng, Xiaoyu Tao, Qi Liu*, Hao Zhang, Yiheng Chen, Defu Lian, Cross-Domain Pre-training with Language Models for Transferable Time Series Representations, ACM WSDM2025: 175–183, Hannover, 2025. [PDF] [Code] [Poster]
  5. Daoyu Wang, Mingyue Cheng*, Zhiding Liu, Qi Liu, TimeDART: A Diffusion Autoregressive Transformer for Self-supervised Time Series Representation, ICML 2025, Vancouver, PMLR 267, 2025. [PDF] [Code]
  6. Jie Ouyang, Tingyue Pan, Mingyue Cheng*, Ruiran Yan, Yucong Luo, Jiaying Lin, Qi Liu, HoH: A Dynamic Benchmark for Evaluating the Impact of Outdated Information on RAG, ACL 2025: 6036–6063, Vienna, 2025. [PDF] [Code]
  7. Mingyue Cheng, Jintao Zhang, Zhiding Liu, Chunli Liu*, A Hybrid Multi-Factor Framework for Dynamic Intraoperative Hypotension Prediction, IJCAI 2025: 4923–4931, Montreal, 2025. [PDF]
  8. Jintao Zhang, Mingyue Cheng*, Xiaoyu Tao, Zhiding Liu, Daoyu Wang, Conditional Denoising Meets Polynomial Modeling: A Flexible Decoupled Framework for Time Series Forecasting, IJCAI 2025: 6993–7001, Montreal, 2025. [PDF] [Code]
  9. Yitong Zhou, Mingyue Cheng*, Qingyang Mao, Feiyang Xu, Xin Li, Enhancing Table Recognition with Vision LLMs: A Benchmark and Neighbor-Guided Toolchain Reasoner, IJCAI 2025: 2503–2511, Montreal, 2025. [PDF] [Code]
  10. Hao Zhang, Mingyue Cheng*, Qi Liu, Zhiding Liu, Linbo Zhu, Yu Su, Towards Automatic Sampling of User Behaviors for Sequential Recommender Systems, IJCAI 2025: 3624–3632, Montreal, 2025. [PDF] [Code]
  11. Jiahao Wang, Mingyue Cheng*, Qingyang Mao, Qi Liu, Feiyang Xu, Xin Li, Enhong Chen, TableTime: Reformulating Time Series Classification as Zero-Shot Table Understanding via LLMs, ACM CIKM 2025. [PDF] [Code]
  12. Shuo Yu, Mingyue Cheng*, Jiqian Yang, Jie Ouyang, et al., Multi-Source Knowledge Pruning for Retrieval-Augmented Generation: A Benchmark and Empirical Study, ACM CIKM 2025.
  13. Zhiding Liu, Mingyue Cheng, Guanhao Zhao, Jiqian Yang, Qi Liu, Enhong Chen, Improving Time Series Forecasting via Instance-aware Post-hoc Revision. (NeurIPS2025) [PDF]
  14. Huijie Liu, Shulan Ruan, Qi Liu, Mingyue Cheng, Zhenya Huang, Yu Liu, Enhong Chen, You He, Global Structure-aware and Feature-augmented Graph Neural Network for Heterophilic Graphs, ACM TOIS. [PDF]
  15. Junhao Yu, Yan Zhuang, Yuxuan Sun, Weibo Gao, Qi Liu, Mingyue Cheng, Zhenya Huang, Enhong Chen, TestAgent: An Adaptive and Intelligent Expert for Human Assessment. (ACL2025) [PDF]
  16. Zirui Liu, Jiatong Li, Yan Zhuang, Qi Liu, Shuanghong Shen, Jie Ouyang, Mingyue Cheng, Shijin Wang, am-ELO: A Stable Framework for Arena-based LLM Evaluation, ICML 2025, PMLR 267, 2025. [PDF]
  17. Mingfan Pan, Qingyang Mao, Xu An, Jianhui Ma, Gang Zhou, Mingyue Cheng, Enhong Chen, Tag-augmented Dual-target Cross-domain Recommendation, RecSys 2025, Prague, 2025.
  18. Yue Chen, Susen Yang, Tong Zhang, Chao Wang, Mingyue Cheng, Chenyi Lei, Han Li, Lasso: Large Language Model-based User Simulator for Cross-Domain Recommendation, RecSys 2025, Prague, 2025.

🐉 Year of the Wood Dragon (Jia Chen Year, 2024)

  1. Jie Ouyang, Yucong Luo, Mingyue Cheng*, Shuo Yu, Daoyu Wang, Qi Liu, Enhong Chen, Revisiting the Solution of Meta KDD Cup 2024: CRAG. (KDD Cup Workshop, 2nd Place in Task 2 & Task 3) [Slides] [Poster]
  2. Mingyue Cheng, Qi Liu*, Wenyu Zhang, Zhiding Liu, Hongke Zhao, Enhong Chen, A General Tail Item Representation Enhancement Framework for Sequential Recommender Systems, Frontier of Computer Science (FCS), 2024, 18(6): 1–12. [PDF] [Code]
  3. Rujiao Zhang, Hao Zhang, Yucong Luo, Zhiding Liu, Mingyue Cheng, Qi Liu, Enhong Chen*, Learning the Dynamics in Sequential Recommendation by Exploiting Real-time Information, ACM CIKM2024: 4288–4292, Oct 2024. [PDF]
  4. Jie Wang, Fajie Yuan, Mingyue Cheng, et al., TransRec: Learning Transferable Recommendation from Mixture-of-Modality Feedback, APWeb-WAIM2024: 193–208, Aug 2024. [PDF]
  5. Zhiding Liu, Jiqian Yang, Mingyue Cheng*, Yucong Luo, Zhi Li, Generative Pretrained Hierarchical Transformer for Time Series Forecasting, ACM SIGKDD2024: 2003–2013, Barcelona, 2024. [PDF]
  6. Yucong Luo, Mingyue Cheng, Hao Zhang, Junyu Lu, Enhong Chen*, Unlocking the Potential of Large Language Models for Explainable Recommendations. (DASFAA2024) [PDF] [Code]
  7. Junzhe Jiang, Shang Qu, Mingyue Cheng*, Qi Liu, et al., Reformulating Sequential Recommendation: Learning Dynamic User Interest with Content-enriched Language Modeling. (DASFAA2024) [PDF] [Code]
  8. Mingyue Cheng, Hao Zhang, Qi Liu*, Fajie Yuan, Zhi Li, Zhenya Huang, Enhong Chen, Longfei Li, Jun Zhou, Empowering Sequential Recommender Systems from Mixture of Collaborative Signals and Semantic Relatedness. (DASFAA2024) [PDF] [Code]
  9. Hao Zhang, Mingyue Cheng*, Qi Liu, Yucong Luo, Rui Li, Enhong Chen, Learning Recommender Systems with Soft Target: A Decoupled Perspective. (DASFAA2024) [PDF] [Code]
  10. Mingyue Cheng, Hao Zhang, Jiqian Yang, Qi Liu*, Li Li, Xin Huang, Liwei Song, Zhi Li, Zhenya Huang, Enhong Chen, Towards Personalized Evaluation of Large Language Models with An Anonymous Crowd-Sourcing Platform. (WWW2024)
  11. Junchen Fu, Fajie Yuan, Yu Song, Zheng Yuan, Mingyue Cheng, et al., Exploring Adapter-based Transfer Learning for Recommender Systems, ACM WSDM'2024: 208–217, Mar 2024. [PDF] [Code]

📘 2023 and Before

  1. Zhiding Liu, Mingyue Cheng, Zhi Li, Zhenya Huang, Qi Liu, Yanhu Xie, Enhong Chen, Adaptive Normalization for Non-stationary Time Series Forecasting: A Temporal Slice Perspective, NeurIPS'2023: 36, New Orleans, 2023. [PDF] [Code]
  2. 耿杰, 刘春丽*, 魏雪梅, 程明月, 袁昆, 李洋, 刘业政, 基于用户重购行为的产品推荐方法, 计算机研究与发展 2023, 60(8): 1795–1807.
  3. Mingyue Cheng, Qi Liu*, Zhiding Liu, Zhi Li, Yucong Luo, Enhong Chen, FormerTime: Hierarchical Multi-scale Representation for Multivariate Time Series Classification, ACM WWW'2023: 1437–1445, Austin, 2023. [PDF] [Code]
  4. Wenqiang He, Mingyue Cheng, Qi Liu*, Zhi Li, ShapeWordNet: An Interpretable Shapelet Neural Network for Physiological Signal Classification, DASFAA'2023: 353–369, Tianjin, 2023.
  5. Mingyue Cheng, Zhiding Liu+, Qi Liu*, Shenyang Ge, Enhong Chen, Towards Automatic Designing of Deep Hybrid Network Architecture for Sequential Recommendation, ACM WWW'2022: 1923–1932. [Code]
  6. Zhiding Liu, Mingyue Cheng, Zhi Li, Qi Liu, Enhong Chen*, One Person, One Model — Learning Compound Router for Sequential Recommendation, IEEE ICDM'2022. [Code]
  7. Junzhe Jiang, Mingyue Cheng, Qi Liu*, Zhi Li, Enhong Chen, Nested Named Entity Recognition from Medical Texts: A Multi-task Learning Approach, CAAI CICAI'2022: 248–259.
  8. Runlong Yu, Qi Liu*, Yuyang Ye, Mingyue Cheng, Enhong Chen, Jianhui Ma, Collaborative List-and-Pairwise Filtering from Implicit Feedback, IEEE TKDE'2022: 34(6): 2667–2680.
  9. Kai Zhang, Qi Liu*, Zhenya Huang, Mingyue Cheng, Kun Zhang, Mengdi Zhang, Wei Wu, Enhong Chen, Graph Adaptive Semantic Transfer for Cross-domain Sentiment Classification, ACM SIGIR'2022: 1566–1576.
  10. Mingyue Cheng, Fajie Yuan+, Qi Liu*, Xin Xin, Enhong Chen, Learning Transferrable User Representations with Sequential Behaviors via Contrastive Pre-training, IEEE ICDM'2021: 51–60.
  11. Mingyue Cheng, Fajie Yuan+, Qi Liu*, Shenyang Ge, Zhi Li, Runlong Yu, Defu Lian, Senchao Yuan, Enhong Chen, Learning Recommender Systems with Implicit Feedback via Soft Target Enhancement, ACM SIGIR'2021: 575–584.
  12. Linan Yue, Qi Liu*, Han Wu, Kai Zhang, Yanqing An, Mingyue Cheng, Biao Yin, Dayong Wu, NeurJudge: A Circumstance-aware Neural Framework for Legal Judgment Prediction, ACM SIGIR'2021: 973–982.
  13. Yanqing An, Qi Liu*, Han Wu, Kai Zhang, Linan Yue, Mingyue Cheng, Hongke Zhao, Senchao Yuan, Enhong Chen, LawyerPAN: A Proficiency Assessment Network for Trial Lawyers, ACM SIGKDD'2021: 5–13.
  14. Mingyue Cheng, Runlong Yu, Qi Liu*, Hongke Zhao, Hefu Zhang, Enhong Chen, Alpha-Beta Sampling for Pairwise Ranking in One-Class Collaborative Filtering, IEEE ICDM'2019: 1000–1005.
  15. 程明月, 刘淇*, 李徵, 于润龙, 高维博, 陈恩红, 多重对级贝叶斯个性化排序算法. (南京信息工程大学学报自然科学版, 2019(03): 302–308)

Open Source Projects

TabClaw 2026.03 GitHub ⭐ …
An open-source framework for agentic table reasoning that enables LLM agents to work over complex tabular data through structured reasoning, tool use, and multi-step decision workflows.
Claw-R1 2026.03 GitHub ⭐ …
An open-source framework for agentic reinforcement learning that extends RL training environments to support reasoning-intensive and tool-using LLM agents.
Mind2Report 2025 GitHub ⭐ …
A deep research agent for synthesizing expert-level commercial and strategic reports from massive web sources with citation-grounded outputs.
Science-Star 2025 GitHub ⭐ …
An open-source framework for scientific AI agents, integrating ReAct-style planning, tool orchestration, memory and reflection, and HLE benchmark support.
Agent-R1 2025 GitHub ⭐ …
A large-model agent training framework for end-to-end RL fine-tuning, supporting GRPO, multi-tool orchestration, long-term memory, and reflective reasoning.

Benchmarks & Datasets

E-Commerce Search · Recall to Relevance
KuaiSearch Search-based Recommendation Paper Dataset 2026.02
KuaiSearch: A Large-Scale E-Commerce Search Dataset for Recall, Ranking, and Relevance is built from real user search interactions on Kuaishou. It preserves authentic user queries and natural-language product texts, covers cold-start users and long-tail products, and spans the three key stages of modern search systems: recall, ranking, and relevance judgment.
Scientific Literature · Agentic Evaluation
PaperArena Scientific Literature Mining Paper Code 2025.10
PaperArena: An Evaluation Benchmark for Tool-Augmented Agentic Reasoning on Scientific Literature benchmarks agentic systems on scientific reading and reasoning with tool use. It targets literature understanding, tool-augmented reasoning, and evidence-grounded evaluation over scientific papers and related scholarly workflows.
AI for Science · Chemical Tables
ChemTable Scientific Literature Mining Paper Dataset 2025.06
Benchmarking Multimodal LLMs on Recognition and Understanding over Chemical Tables introduces ChemTable, a real-world benchmark curated from chemical literature. It supports two core tasks: table recognition and table understanding, with expert annotations over cell polygons, logical layouts, and chemistry-specific semantic labels such as reagents, catalysts, yields, and graphical components.
RAG Evaluation · Dynamic Benchmark
HoH RAG Paper Code 2025.05
HoH: A Dynamic Benchmark for Evaluating the Impact of Outdated Information on RAG studies how retrieval-augmented generation systems fail when knowledge becomes stale. It provides a dynamic evaluation setting for measuring temporal robustness, outdated-information sensitivity, and the impact of knowledge freshness in modern RAG pipelines.

Education

Working Experiences

Teaching

Honors and Awards

Service

Program Committee Member
  • ACM International World Wide Web Conference (TheWebConf): 2024, 2025
  • ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD): 2023, 2024, 2025
  • International Conference on Learning Representations (ICLR): 2025
  • International Conference on Machine Learning (ICML): 2025
  • Conference on Neural Information Processing Systems (NeurIPS): 2024, 2025
  • Annual Meeting of the Association for Computational Linguistics (ACL): 2025
  • International Joint Conference on Artificial Intelligence (IJCAI): 2024, 2025, 2026 (SPC)
  • International Conference on Web Search and Data Mining (WSDM): 2025
  • SIAM International Conference on Data Mining (SDM): 2024
  • ACM International Conference on Information and Knowledge Management (CIKM): 2024, 2025
  • Database Systems for Advanced Applications (DASFAA): 2024, 2025
  • IEEE Task Force on AI for Time Series and Spatio-Temporal Data
Journal Reviewer
  • IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE)
  • IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)
  • IEEE Transactions on Neural Network and Learning Systems (IEEE TNNLS)
  • IEEE Transactions on Audio, Speech and Language Processing (IEEE T-ASL)
  • ACM Transactions on Knowledge Discovery from Data (TKDD)
  • ACM Transactions on Intelligent Systems and Technology (TIST)
  • Transactions on Machine Learning Research (TMLR)
  • Neurocomputing
  • Frontiers of Computer Science (FCS)
  • 软件学报
  • 计算机学报

Research Grants

Related Links

Prof. Qi Liu
University of Science and Technology of China
USTC
Prof. Enhong Chen
University of Science and Technology of China
USTC
Prof. Fajie Yuan
Westlake University
WU
Prof. Hongke Zhao
Tianjin University
TJU