PPaperPicks

Quanming Yao

24 papers at tracked venues · 20 at CORE A* · active 20242026

Venues

Frequent coauthors

Papers

  1. DA-RAG: Dynamic Attributed Community Search for Retrieval-Augmented Generation
  2. Efficient Reinforcement Learning for Zero-Shot Coordination in Evolving Games
  3. Adaptive Preference Arithmetic: A Personalized Agent with Adaptive Preference Arithmetic for Dynamic Preference Modeling
  4. Automated Decision-Making on Networks with LLMs through Knowledge-Guided Evolution
  5. Curriculum-aware Training for Discriminating Molecular Property Prediction Models
  6. Erasing Concept Combination from Text-to-Image Diffusion Model
  7. Explore the Disentanglement Mechanism for Deep Learning
  8. Hierarchical Graph Tokenization for Molecule-Language Alignment
  9. Learning to Learn with Contrastive Meta-Objective
  10. Nested-Refinement Metamorphosis: Reflective Evolution for Efficient Optimization of Networking Problems
  11. PERSCEN: Learning Personalized Interaction Pattern and Scenario Preference for Multi-Scenario Matching
  12. Superpose Task-specific Features for Model Merging
  13. Think Both Ways: Teacher-Student Bidirectional Reasoning Enhances MCQ Generation and Distractor Quality
  14. Unified Molecule-Text Language Model with Discrete Token Representation
  15. Why In-Context Learning Models are Good Few-Shot Learners?
  16. Customized Subgraph Selection and Encoding for Drug-drug Interaction Prediction
  17. Heuristic Learning with Graph Neural Networks: A Unified Framework for Link Prediction
  18. Knowledge-Enhanced Recommendation with User-Centric Subgraph Network
  19. Less is More: One-shot Subgraph Reasoning on Large-scale Knowledge Graphs
  20. PACIA: Parameter-Efficient Adapter for Few-Shot Molecular Property Prediction
  21. Robust Communicative Multi-Agent Reinforcement Learning with Active Defense
  22. Towards Human-like Learning from Relational Structured Data
    AAAI 2024 · Quanming Yao
  23. Understanding Expressivity of GNN in Rule Learning
  24. Warming Up Cold-Start CTR Prediction by Learning Item-Specific Feature Interactions