Mingyue Cheng

Mingyue Cheng Ph.D.  ·  Associate Researcher

Cognitive intelligence: understanding, reasoning, and interaction.

State Key Laboratory of Cognitive Intelligence
School of Computer Science and Technology,  University of Science and Technology of China
USTC-AGI Group Google Scholar GitHub CV (PDF)
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, University of Science and Technology of China (USTC), affiliated with the State Key Laboratory of Cognitive Intelligence. I received my Ph.D. in Computer Science and Technology from USTC in 2023, supervised by Prof. Qi Liu. My research is conducted in collaboration with Prof. Enhong Chen and Prof. Qi Liu.

Research Interests

My research focuses on cognitive intelligence, with LLM agents and autonomous learning as general mechanisms and time series, scientific literature, and tools as core research objects. I study how intelligent systems reason, interact, and improve through experience.

  • LLMs and Agentic AI: Reinforcement learning, memory, and tool-augmented reasoning for autonomous agents that learn through interaction.
  • Time Series Mining: Context-aware forecasting and reasoning, with applications in electricity load, power generation, and weather prediction.
  • Scientific Literature Mining: Scientific retrieval, multimodal document understanding, knowledge extraction, and cross-paper reasoning grounded in evidence.

Applications: AI for Science (scientific literature and tool mining), Personalized Intelligence, and Forecasting Intelligence.

Research overview & representative work →

For research opportunities and collaboration, visit the USTC-AGI Group or email me.

Latest News

  • [Nov. 2026] 🎉 Congratulations on our papers AdaCast, PaperArena, and SheetCompass being accepted to ACM WSDM 2027!
  • [Oct. 2026] 🎉 I will serve as an Area Chair (AC) for ICML 2027.
  • [Oct. 2026] 🎉 I will serve as an Area Chair (AC) for The Web Conference 2027 (WWW 2027).
  • [Sep. 2026] 🎉 Congratulations on our demo papers CastClaw and AgentWorld being accepted to the IEEE ICDM 2026 Demo Track!
  • [Sep. 2026] 🎉 Congratulations on our survey A Comprehensive Survey of Time Series Forecasting: Concepts, Challenges, and Future Directions being accepted by IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE)!
  • [Aug. 2026] 🎉 Congratulations on our paper PaperScout being accepted to Findings of EMNLP 2026!
  • [Aug. 2026] 🎉 We are excited to present our tutorial, “Context-Aware Time Series Forecasting: From Pattern Extrapolation to Cognitive Reasoning,” at IEEE ICDM 2026. See you in Shenyang!
  • [Aug. 2026] 🎉 I will serve as the Publication Chair for ICEBE 2026.
  • [Aug. 2026] 🎉 Congratulations on our papers Mind2Report, Time-R1, and AlphaCast being accepted to ACM CIKM 2026!
  • [Aug. 2026] 🎉 Congratulations on our survey A Survey on Table Mining with Large Language Models: Challenges, Advancements and Prospects being accepted by ACM Computing Surveys (ACM CSUR)!
  • [Aug. 2026] 🎉 Congratulations on our demo papers Agent-R1 and TabClaw being accepted to the ACM CIKM 2026 Demo Track!
  • [Jul. 2026] Our tutorial on Context-Aware Time Series Forecasting has been accepted by the IEEE ICDM 2026 Industry Tutorial Session. I will serve as a tutorial organizer and speaker.
  • [Jul. 2026] Our workshop, FedKDD/FedMAS 2026, will be held in conjunction with KDD 2026. I am honored to serve as the Program Chair.
  • [Jul. 2026] 🏆 Our Agentic Time Series Forecasting solution CastStar ranked #1 on the GIFT-Eval Overall leaderboard.
  • [Jun. 2026] 🎉 Our project CastClaw（星辰） received a Poster Presentation Certificate at the 2026 BAAI Conference Agent for Science Competition.
  • [Jun. 2026] 🎉 Congratulations on our Knowledge-Oriented RAG Survey being accepted to ACM Transactions on Information Systems (ACM TOIS)!
  • [May. 2026] 🎉 Congratulations to Zhiding Liu on his work DisenTS being accepted to IEEE Transactions on Pattern Analysis and Machine Intelligence (IEEE TPAMI)!
  • [May. 2026] 🎉 Congratulations to Xiaoyu Tao on her paper being accepted to ACM Transactions on Intelligent Systems and Technology (ACM TIST)!
  • [May. 2026] 🎉 Congratulations to two of my co-supervised students (Yucong Luo and Jie Ouyang) on receiving ByteDance Jindouyun offers!
  • [May. 2026] 🎉 Congratulations to Yitong Zhou on our paper ChemTable being accepted to KDD 2026!
  • [May. 2026] 🚀 We released CastFactory（炼星坊）, a framework for LLM-driven time series forecasting model training. GitHub
  • [May. 2026] 🎉 Congratulations to Xiaoyu Tao and Bohou Zhang on our papers (TokenCast and ScholarSum) being accepted to IJCAI 2026!
  • [May. 2026] 🎉 Congratulations to Yaguo Liu and Xiaoyu Tao on our papers (CoGenCast and MemCast) being accepted to ICML 2026!
  • [Apr. 2026] 📄 We released the preprint version of our survey on LLM-based agents from the contextual cognition perspective on Preprints.org: "A Comprehensive Survey of the LLM-Based Agent: The Contextual Cognition Perspective".
View All News →

Publications

(* Corresponding Author, + Equal Contribution)

Browse publications →

  1. Zhiding Liu+, Jiqian Yang+, Mingyue Cheng*, Zhi Li*, Enhong Chen*, World2TS: Real-World Event Context for Time-Series Forecasting. (Preprint) [arXiv] [Website]
  2. Mingyue Cheng, Xiaoyu Tao, Qi Liu, Ze Guo, Enhong Chen, Position: Beyond Model-Centric Prediction — Agentic Time Series Forecasting. (Preprint) [PDF]
  3. Xiaoyu Tao, Mingyue Cheng, Chuang Jiang, Tian Gao, Huanjian Zhang, Yaguo Liu, Qi Liu, Cast-R1: Learning Tool-Augmented Sequential Decision Policies for Time Series Forecasting. (Preprint) [PDF] [Code]
  4. Xiaoyu Tao, Mingyue Cheng, Bokai Pan, Chuang Jiang, Huanjian Zhang, Tian Gao, Yaguo Liu, Qi Liu, Enhong Chen, CastFSR: A Fast--Slow--Reflect Agentic Reasoning Framework for Context-Aware Time Series Forecasting. (Preprint) [ArXiv]
  5. Ze Guo, Mingyue Cheng, Xiaoyu Tao, Shuo Yu, Shangtong Ye, NeoResearch: Literature- and Experience-Guided Autonomous Time Series Model Discovery. (under review)
  6. Bokai Pan, Ruijie Yang, Mingyue Cheng, Jiahao Wang, Xiaoyu Tao, CastWorld: Benchmarking Context-Aware Agentic Time Series Forecasting Beyond Predictive Accuracy. (under review)
  7. Bokai Pan, Mingyue Cheng*, Zhiding Liu, Shuo Yu, Xiaoyu Tao, Yuchong Wu, Qi Liu, Defu Lian, Enhong Chen, CastFlow: Learning Role-Specialized Agentic Workflows for Time Series Forecasting. (Preprint) [PDF] [Code]
  8. Daoyu Wang, Qingchuan Li, Mingyue Cheng, Jie Ouyang, Shuo Yu, Qi Liu, Enhong Chen, StepPO: Step-Aligned Policy Optimization for Agentic Reinforcement Learning. (Preprint) [PDF]
  9. Mingyue Cheng, Daoyu Wang, Shuo Yu, Qingchuan Li, Jie Ouyang, Yucong Luo, Yiju Zhang, Qi Liu*, Enhong Chen, A Comprehensive Survey of the LLM-Based Agent: The Contextual Cognition Perspective. (Preprint) [Preprint]

  1. Mingyue Cheng, Xiaoyu Tao, Ze Guo, Qi Liu*, Bokai Pan, Shangtong Ye, Shijin Wang, Enhong Chen, One Forecast, One World: Adaptive Evidence Reasoning for Context-Aware Time Series Forecasting (AdaCast). ACM WSDM 2027 Accepted.
  2. Daoyu Wang, Mingyue Cheng*, Shuo Yu, Zirui Liu, Ze Guo, Xin Li, Qi Liu, PaperArena: An Evaluation Benchmark for Tool-Augmented Agentic Reasoning on Scientific Literature. ACM WSDM 2027 Accepted. [PDF] [Code]
  3. Panjing He, Mingyue Cheng*, Yucong Luo, Li Li, Xiaohan Zhang, SheetCompass: Hierarchical Relation Graphs for Agentic Spreadsheet Reasoning. ACM WSDM 2027 Accepted. [PDF] [Code]

  1. Mingyue Cheng, Yucong Luo, Jie Ouyang, Qi Liu*, Huijie Liu, Li Li, Shuo Yu, Bohou Zhang, Jiawei Cao, Jie Ma, Daoyu Wang, Enhong Chen, A Survey on Knowledge-Oriented Retrieval-Augmented Generation. ACM Transactions on Information Systems (ACM TOIS) Accepted. [PDF] [Code]
  2. 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. IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE) Accepted. [PDF] [Code]
  3. 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. ACM Computing Surveys (ACM CSUR) Accepted. [PDF] [Code]
  4. Tingyue Pan, Mingyue Cheng*, Shilong Zhang, Zhiding Liu, Xiaoyu Tao, Yucong Luo, Jintao Zhang, Qi Liu, OneCast: Structured Decomposition and Modular Generation for Cross-Domain Time Series Forecasting. ACM Transactions on Knowledge Discovery from Data (ACM TKDD) Accepted. [PDF]
  5. Mingyue Cheng, Daoyu Wang, Qi Liu*, Shuo Yu, Xiaoyu Tao, Yuqian Wang, Chengzhong Chu, Yu Duan, Mingkang Long, Enhong Chen, Mind2Report: A Cognitive Deep Research Agent for Expert-Level Commercial Report Synthesis. ACM CIKM 2026 Accepted. [PDF] [Code]
  6. 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. ACM CIKM 2026 Accepted. [PDF] [Code]
  7. Xiaohan Zhang, Tian Gao, Mingyue Cheng*, Bokai Pan, Ze Guo, Yaguo Liu, Xiaoyu Tao, Qi Liu, AlphaCast: A Human Wisdom-LLM Intelligence Co-Reasoning Framework for Interactive Time Series Forecasting. ACM CIKM 2026 Accepted. [PDF] [Code]
  8. Mingyue Cheng, Xiaoyu Tao, Huajian Zhang, Qi Liu*, Enhong Chen, InstructTime++: Time Series Classification with Multimodal Language Modeling via Implicit Feature Enhancement. ACM Transactions on Intelligent Systems and Technology (ACM TIST) Accepted. [PDF] [Code]
  9. Yitong Zhou, Mingyue Cheng*, Qingyang Mao, Yucong Luo, Qi Liu, Yupeng Li, Xiaohan Zhang, Deguang Liu, Xin Li, Enhong Chen, Benchmarking Multimodal LLMs on Recognition and Understanding over Chemical Tables. KDD 2026 Accepted. [PDF] [Code]
  10. Xiaoyu Tao, Mingyue Cheng*, Ze Guo, Shuo Yu, Yaguo Liu, Qi Liu, Shijin Wang, MemCast: Memory-Driven Time Series Forecasting with Experience-Conditioned Reasoning. ICML 2026 Accepted. [PDF]
  11. Mingyue Cheng, Yaguo Liu, Daoyu Wang, Xiaoyu Tao, Qi Liu*, CoGenCast: A Coupled Autoregressive-Flow Generative Framework for Time Series Forecasting. ICML 2026 Accepted. [PDF]
  12. Xiaoyu Tao, Shilong Zhang, Mingyue Cheng*, Daoyu Wang, Tingyue Pan, Bokai Pan, Changqing Zhang, Shijin Wang, From Values to Tokens: An LLM-Driven Framework for Context-aware Time Series Forecasting via Symbolic Discretization. IJCAI 2026 Accepted. [PDF]
  13. Bohou Zhang, Xiaoyu Tao, Mingyue Cheng*, Huijie Liu, Qi Liu, ScholarSum: Student-Teacher Abstractive Summarization via Knowledge Graph Reasoning and Reflective Refinement. IJCAI 2026 Accepted.
  14. Jiawei Cao, Jie Ouyang, Mingyue Cheng*, Zhaomeng Zhou, Chunli Liu, Yupeng Li, Zirui Liu, Shijin Wang, Re3: Relevance & Recency Retrieval for Mitigating Temporal Hallucination. ACL 2026 Accepted.
  15. Huajian Zhang, Mingyue Cheng*, Yucong Luo, Xiaoyu Tao, STaR: Towards Cognitive Table Reasoning via Slow-Thinking Large Language Models. ACM WWW 2026. [PDF] [Code]
  16. 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 WWW 2026. [PDF]
  17. 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 WWW 2026. [PDF]
  18. 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. ACM WSDM 2026: 99–110, Feb 2026. [PDF] [Code]
  19. 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 WSDM 2026: 498–508, Feb 2026. [arXiv version] [Code]
  20. Chuang Jiang, Mingyue Cheng*, Xiaoyu Tao, Qingyang Mao, Jie Ouyang and Qi Liu, TableMind: An Autonomous Programmatic Agent for Tool-Augmented Table Reasoning. ACM WSDM 2026: 260–270, Feb 2026. [PDF] [Code]
  21. 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. AAAI 2026: 31671–31679, Mar 2026. [PDF]
  22. 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. AAAI 2026: 15189–15197, Mar 2026. [PDF]
  23. Tingyue Pan, Jie Ouyang, Mingyue Cheng, Qingchuan Li, Zirui Liu, Daoyu Wang, Mingfan Pan, Shuo Yu, Qi Liu, PaperScout: An Autonomous Agent for Academic Paper Search with Process-Aware Sequence-Level Policy Optimization. Findings of EMNLP 2026 Accepted. [PDF]
  24. Xiaoyu Tao, Mingyue Cheng, Ze Guo, Bokai Pan, Qi Liu, Shijin Wang, Enhong Chen, CastClaw: A Human-in-the-Loop Autonomous Agent for Interactive Time Series Forecasting. IEEE ICDM 2026 Demo Track Accepted. [Code]
  25. Daoyu Wang, Mingyue Cheng, Qingchuan Li, Shuo Yu, Jie Ouyang, Qi Liu, Enhong Chen, AgentWorld: A Data Factory for Training LLM Agents from Multi-Turn Interactions. IEEE ICDM 2026 Demo Track Accepted. [Code]
  26. Mingyue Cheng, Shuo Yu, Daoyu Wang, Qingchuan Li, Xiaoyu Tao, Jie Ouyang, Yucong Luo, Yitong Zhou, Qi Liu*, Enhong Chen, Agent-R1: A Unified and Modular Framework for Agentic Reinforcement Learning. ACM CIKM 2026 Demo Track Accepted.
  27. Mingyue Cheng, Shuo Yu, Daoyu Wang, Qingchuan Li, Xiaoyu Tao, Qingyang Mao, Yitong Zhou, Qi Liu*, TabClaw: An Interactive and Self-Evolving Agent for Spreadsheet Manipulation and Table Reasoning. ACM CIKM 2026 Demo Track Accepted.

  1. Mingyue Cheng, Jiqian Yang, Tingyue Pan, Qi Liu*, Zhi Li, ConvTimeNet: A Deep Hierarchical Fully Convolutional Model for Multivariate Time Series Analysis, ACM WWW 2025, 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 Transactions on Intelligent Systems and Technology (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 WSDM 2025 (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 WSDM 2025: 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.

  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, Frontiers 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 CIKM 2024: 4288–4292, Oct 2024. [PDF]
  4. Jie Wang, Fajie Yuan, Mingyue Cheng, et al., TransRec: Learning Transferable Recommendation from Mixture-of-Modality Feedback, APWeb-WAIM 2024: 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 SIGKDD 2024: 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. (DASFAA 2024) [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. (DASFAA 2024) [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. (DASFAA 2024) [PDF] [Code]
  9. Hao Zhang, Mingyue Cheng*, Qi Liu, Yucong Luo, Rui Li, Enhong Chen, Learning Recommender Systems with Soft Target: A Decoupled Perspective. DASFAA 2024, LNCS 14852, Gifu, Japan, 2024. [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. (WWW 2024)
  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]

  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 Transactions on Knowledge and Data Engineering (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)

Systems Product

科言乐问

科言 · Science Intelligence

Discover scientific literature through quick search and in-depth retrieval.

lewen.bdaa.pro Visit website

科言文修

科言 · Science Intelligence

Support academic writing with polishing, proofreading, and translation tools.

writelearn.bdaa.pro Visit website

Open Project

LLMs and Agentic AI

Agent-R1
2025.04 CIKM 2026 GitHub Website Docs 1661
A modular reinforcement learning framework for training LLM agents through multi-turn interactions.
Claw-R1
2026.03 GitHub Website 194
A data infrastructure for collecting, evaluating, and curating multi-turn interactions to train LLM agents.

Time Series Intelligence（科语）

CastClaw（星辰）
2026.04 GitHub Website Docs 47
A human-in-the-loop agent framework for interactive time series forecasting and research.

Science Intelligence（Scientific Tool and Knowledge）

PaperScout（科言乐问）
2026.01 EMNLP 2026 GitHub Website Paper 9
An autonomous scientific literature retrieval agent that refines search strategies through multi-turn interaction.
Academic Search
2026.04 GitHub 616
A literature search tool for AI agents, supporting scholarly retrieval, metadata verification, and BibTeX export.
All projects & technical details →

Benchmarks & Datasets

Time Series Intelligence（Context-aware Time Series Forecasting）

Time Series Intelligence · Real-world Event Context
World2TS Paper
2026.10 Website GitHub Dataset
A human-reviewed dataset linking time series across six domains to real-world events for context-aware forecasting.

Science Intelligence（Scientific Tool and Knowledge）

Scientific Literature · Agentic Evaluation
PaperArena Scientific Literature Mining Paper
2025.10 WSDM 2027 Website GitHub 18
A benchmark for evaluating tool-augmented agentic reasoning over scientific literature.
AI for Science · Chemical Tables
ChemTable Scientific Literature Mining Paper
2025.06 KDD 2026 GitHub 8
A benchmark for recognizing and understanding chemical tables in scientific literature.

Retrieval & Recommendation

E-Commerce Search · Recall to Relevance
KuaiSearch Search-based Recommendation Paper
2026.02 Website GitHub 31
A large-scale e-commerce search dataset covering retrieval, ranking, and relevance assessment.
RAG Evaluation · Dynamic Benchmark
HoH Retrieval-Augmented Generation Paper
2025.06 ACL 2025 GitHub 7
A dynamic benchmark for evaluating how outdated information affects retrieval-augmented generation.
All benchmarks & datasets →

Education

Professional Experience

  • Jun. 2023 ~ Present, Associate Researcher, School of Computer Science and Technology, USTC, Hefei, China
  • Jan. 2021 ~ Jun. 2023, Research Assistant, Research Center for Big Data in Intelligent Healthcare, USTC, Hefei, China
  • Jun. 2019 ~ Oct. 2019, Research Intern, Data Service Center (DSC), Platform and Content Group (PCG), Tencent, Shenzhen, China
  • Jul. 2018 ~ Sep. 2018, Engineer Intern, Lab of Big Data, Core Technology R&D Platform, iFLYTEK, Hefei, China

Teaching

  • Introduction to Data Science — Undergraduate course, Spring 2024, 2025, and 2026.
  • Introduction to Systems Programming — Undergraduate course, Spring 2026.

Selected Honors and Awards

  • Aug. 2025, USTC Hongzhuan Young Talent
  • Mar. 2025, Best of WSDM 2025 (Outstanding Paper Award)
  • Dec. 2024, Gold Award, Ascend AI Innovation Competition National Finals (Advisor)
  • Aug. 2024, Second Place in Task 2 & Task 3, KDD Cup 2024
  • Dec. 2023, National Silver Award, China International College Students’ Innovation Competition 2023 (Ministry of Education)
All honors & awards →

Professional Service

  • Area Chair: WWW, ICML, and ICLR 2027.
  • Senior Program Committee: IJCAI 2026.
  • Program Chair: FedKDD/FedMAS Workshop at KDD 2026.
  • Tutorial Organizer and Speaker: Context-Aware Time Series Forecasting, IEEE ICDM 2026.
  • Publication Chair: IEEE ICEBE 2026.
  • Program Committee: KDD, WWW, WSDM, CIKM, NeurIPS, ACL, and other conferences.
  • Reviewer: TKDE, TPAMI, TNNLS, TKDD, TIST, TMLR, and other journals.
Full academic service →

Research Grants

  • 2027–2028 · USTC Youth Innovation Fund · Project Lead — Multi-turn agent learning and continual evolution. Upcoming
  • 2026–2028 · National Science and Technology Major Project · Core Member — Scientific data governance for chemistry. Ongoing
  • 2026–2029 · CAS Strategic Priority Research Program (Category B) · Project Lead — Autonomous interactive learning. Ongoing
  • 2026–2028 · NSFC Young Scientists Fund (Category C) · Project Lead — Context-aware time series learning and forecasting. Ongoing
  • 2025–2026 · USTC New Medicine Joint Fund · Project Lead — Time series modeling for perioperative care. Ongoing
  • 2024–2026 · Anhui Provincial Natural Science Foundation · Project Lead — Scientific table understanding and reasoning. Period ended
Project details →

My research is also partially supported by industry grants from:

Related Links