PPaperPicks

Jun Wang

OPPO Research Institute, China

23 papers at tracked venues · 17 at CORE A* · active 20242026

Venues

Frequent coauthors

Papers

  1. ColorBench: Benchmarking Mobile Agents with Graph-Structured Framework for Complex Long-Horizon Tasks
  2. ColorBrowserAgent: Complex Long-Horizon Browser Agent with Adaptive Knowledge Evolution
  3. Compiling Activation Steering into Weights via Null-Space Constraints for Stealthy Backdoors
  4. Discrete Preference Learning for Personalized Multimodal Generation
  5. Does LLM Focus on the Right Words? Mitigating Context Bias in LLM-based Recommenders
  6. Field Matters: A Lightweight LLM-enhanced Method for CTR Prediction
  7. FraudShield: Knowledge Graph Empowered Defense for LLMs against Fraud Attacks
  8. Sharpness-Aware Minimization for Generalized Embedding Learning in Federated Recommendation
  9. SpecTran: Spectral-Aware Transformer-based Adapter for LLM-Enhanced Sequential Recommendation
  10. Diversity-Aware Self-Paced Data Selection for LLM Fine-Tuning
  11. FedGF: Enhancing Structural Knowledge via Graph Factorization for Federated Graph Learning
  12. FedGOG: Federated Graph Out-of-Distribution Generalization with Diffusion Data Exploration and Latent Embedding Decorrelation
  13. HammerBench: Fine-Grained Function-Calling Evaluation in Real Mobile Assistant Scenarios
    ACL 2025 · Jun Wang
  14. Joint Item Embedding Dual-view Exploration and Adaptive Local-Global Fusion for Federated Recommendation
  15. Joint Similarity Item Exploration and Overlapped User Guidance for Multi-Modal Cross-Domain Recommendation
  16. MSL: Not All Tokens Are What You Need for Tuning LLM as a Recommender
  17. Personalized Federated Recommendation with Multi-Faceted User Representation and Global Consistent Prototype
  18. Progressive Tasks Guided Multi-Source Network for Customer Lifetime Value Prediction in Online Advertising
  19. Sim4Rec: Data-Free Model Extraction Attack on Sequential Recommendation
  20. Training-free Periodic Interest Augmentation in Incremental Recommendation
  21. DIIT: A Domain-Invariant Information Transfer Method for Industrial Cross-Domain Recommendation
  22. Distillation Matters: Empowering Sequential Recommenders to Match the Performance of Large Language Models
  23. FOOGD: Federated Collaboration for Both Out-of-distribution Generalization and Detection