Yong Yu
Distinguished Professor
Leads the APEX Data & Knowledge Management Lab, working on machine learning, data mining and recommender systems.
Yong Yu's lab at SJTU works on recommendation, search & web, data management & big data and knowledge, QA & retrieval. 110 papers since 2023, 69 at top venues, mostly KDD and WWW. Applications close .
At a glance
- papers, 2023–2026
- 29/ year
- at T1 venues
- 63%
- PhD students
- —
- MS students
- —
- alumni listed
- —
Papers by yearfrom DBLP, 2023–2026
- 25 papers2026 · T1 16 · collecting
- 32 papers2025 · T1 17
- 25 papers2024 · T1 15
- 28 papers2023 · T1 21
T1 venuesOtherVenues: KDD, WWW, CIKM, ACL, AAAI
Research focuspaper titles that use each topic's words
- Recommendation, search & web38 papers
- Knowledge, QA & retrieval18 papers
- recommender14 papers
- Data management & big data8 papers
- knowledge management0 papers
Paper list
From DBLP.
202625 papers
- ACL (T1)A Comprehensive Survey of Process Reward Models: Data Generation, Model Construction, and Usage (opens in a new tab)
- ACM Trans. Inf. Syst.A Comprehensive Survey on Retrieval Methods in Recommender Systems (opens in a new tab)
- ACL (T1)A Survey of Large Language Model-Based Search Agents (opens in a new tab)
- ICLR (T1)ATGen: Adversarial Reinforcement Learning for Test Case Generation (opens in a new tab)
- Findings of ACLAttribution-Based Analysis and Optimization of Modular Agentic Workflows (opens in a new tab)
- AAMAS (T1)Automatically Benchmarking LLM Code Agents through Agent-driven Annotation and Evaluation (opens in a new tab)
- WWW (T1)ColorBench: Benchmarking Mobile Agents with Graph-Structured Framework for Complex Long-Horizon Tasks (opens in a new tab)
- ACL (T1)CoreCodeBench: Decoupling Code Intelligence via Fine-Grained Repository-Level Tasks (opens in a new tab)
- AAMAS (T1)DebugTA: An LLM-Based Agent for Simplifying Debugging and Teaching in Programming Education (opens in a new tab)
- ECML-PKDDDiffCold: A Diffusion-Based Generative Model for Cold-Start Item Recommendation (opens in a new tab)
- KDD (T1)DynaTree: Dynamic Agentic Retrieval Tree for Time-Sensitive News Retrieval (opens in a new tab)
- Trans. Recomm. Syst.Efficient and Deployable Knowledge Infusion for Open-World Recommendations via Large Language Models (opens in a new tab)
202532 papers
- SIGIR (T1)Action First: Leveraging Preference-Aware Actions for More Effective Decision-Making in Interactive Recommender Systems (opens in a new tab)
- ECML-PKDDAdvKT: An Adversarial Multi-step Training Framework for Knowledge Tracing (opens in a new tab)
- KDD (T1)An Automatic Graph Construction Framework based on Large Language Models for Recommendation (opens in a new tab)
- ICICAn Efficient Approximation Framework for LLM-Enhanced Recommendation (opens in a new tab)
- AAAI (T1)Beyond Graph Convolution: Multimodal Recommendation with Topology-aware MLPs (opens in a new tab)
- Findings of ACLBoost, Disentangle, and Customize: A Robust System2-to-System1 Pipeline for Code Generation (opens in a new tab)
- KDD (T1)Bursting Filter Bubble: Enhancing Serendipity Recommendations with Aligned Large Language Models (opens in a new tab)
- IJCNNCECAT: Certainty-Guaranteed Environment for Computerized Adaptive Testing (opens in a new tab)
- Findings of ACLCodePRM: Execution Feedback-enhanced Process Reward Model for Code Generation (opens in a new tab)
- ICONIPContext-Aware Policy-Guided Gradient Search for Offline Model-Based Optimization (opens in a new tab)
- WWW (T1)D2K: Turning Historical Data into Retrievable Knowledge for Recommender Systems (opens in a new tab)
- ACL (T1)DebateCoder: Towards Collective Intelligence of LLMs via Test Case Driven LLM Debate for Code Generation (opens in a new tab)
202425 papers
- CCIRA Dual-Aligned Model for Multimodal Recommendation (opens in a new tab)
- ACM Trans. Knowl. Discov. DataA Survey on Bid Optimization in Real-Time Bidding Display Advertising (opens in a new tab)
- ICONIPAdaptive Retrieval-Based Gradient Planning for Offline Multi-context Model-Based Optimization (opens in a new tab)
- CIKM (T1)AlignRec: Aligning and Training in Multimodal Recommendations (opens in a new tab)
- WWW (T1)ClickPrompt: CTR Models are Strong Prompt Generators for Adapting Language Models to CTR Prediction (opens in a new tab)
- CIKM (T1)ELCoRec: Enhance Language Understanding with Co-Propagation of Numerical and Categorical Features for Recommendation (opens in a new tab)
- RecSys (T1)FLIP: Fine-grained Alignment between ID-based Models and Pretrained Language Models for CTR Prediction (opens in a new tab)
- WWW (T1)HiFI: Hierarchical Fairness-aware Integrated Ranking with Constrained Reinforcement Learning (opens in a new tab)
- WWW (T1)InfoRank: Unbiased Learning-to-Rank via Conditional Mutual Information Minimization (opens in a new tab)
- ICANNInvariant Graph Contrastive Learning for Mitigating Neighborhood Bias in Graph Neural Network Based Recommender Systems (opens in a new tab)
- DAILooking Ahead to Avoid Being Late: Solving Hard-Constrained Traveling Salesman Problem (opens in a new tab)
- WWW (T1)M-scan: A Multi-Scenario Causal-driven Adaptive Network for Recommendation (opens in a new tab)
202328 papers
- WSDM (T1)A Bird's-eye View of Reranking: From List Level to Page Level (opens in a new tab)
- JMLR (T1)Adaptation Augmented Model-based Policy Optimization (opens in a new tab)
- DAIAdaptive Control Strategy for Quadruped Robots in Actuator Degradation Scenarios (opens in a new tab)
- DAIAdversarially Trained Environment Models Are Effective Policy Evaluators and Improvers - An Application to Information Retrieval (opens in a new tab)
- TKDE (T1)AIM: Automatic Interaction Machine for Click-Through Rate Prediction (opens in a new tab)
- WSDM (T1)An F-shape Click Model for Information Retrieval on Multi-block Mobile Pages (opens in a new tab)
- WSDM (T1)AutoGen: An Automated Dynamic Model Generation Framework for Recommender System (opens in a new tab)
- DAID4W: Dependable Data-Driven Dynamics for Wheeled Robots (opens in a new tab)
- KDD (T1)Deep Landscape Forecasting in Multi-Slot Real-Time Bidding (opens in a new tab)
- KDD (T1)GMOCAT: A Graph-Enhanced Multi-Objective Method for Computerized Adaptive Testing (opens in a new tab)
- CIKM (T1)Graph Enhanced Hierarchical Reinforcement Learning for Goal-oriented Learning Path Recommendation (opens in a new tab)
- TKDE (T1)Large-Scale Interactive Recommendation With Tree-Structured Reinforcement Learning (opens in a new tab)
Where alumni went
Alumni are not listed on the lab homepage.
Apply to SJTUFall 2027
Computer Science PhD (international applicants)
- Round
- Self-funded
- Opens
- —
- GRE
- See program page
- English
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- Fee
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Not yet confirmed for this intake.
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