PPaperPicks

Zhewei Wei

33 papers at tracked venues · 28 at CORE A* · active 20242026

Venues

Frequent coauthors

Papers

  1. AbFlow: End-to-end Paratope-Centric Antibody Design by Interaction Enhanced Flow Matching
  2. AeroSketch: Near-Optimal Time Matrix Sketch Framework for Persistent, Sliding Window, and Distributed Streams
  3. GRAPHIA: Harnessing Social Graph Data to Enhance LLM-Based Social Simulation
  4. MotifAgent: Learning Molecular Assembly through Multi-Agent Collaboration for Chemical Language Understanding
  5. Personal 3D Printing without Visual Dependency in the Generative AI Era: Opportunities and Challenges
  6. Advancing Retrosynthesis with Retrieval-Augmented Graph Generation
  7. Dimension-Free Adaptive Subgradient Methods with Frequent Directions
  8. Efficiency Unleashed: Inference Acceleration for LLM-based Recommender Systems with Speculative Decoding
  9. Fast Second-Order Online Kernel Learning Through Incremental Matrix Sketching and Decomposition
  10. Future Link Prediction Without Memory or Aggregation
  11. LLM-Based Multi-Agent Systems are Scalable Graph Generative Models
  12. Large-Scale Spectral Graph Neural Networks via Laplacian Sparsification
  13. Lighter-X: An Efficient and Plug-and-play Strategy for Graph-based Recommendation through Decoupled Propagation
  14. Mixing Time Matters: Accelerating Effective Resistance Estimation via Bidirectional Method
  15. NeutronTask: Scalable and Efficient Multi-GPU GNN Training with Task Parallelism
  16. Position: Spectral GNNs Rely Less on Graph Fourier Basis than Conceived
  17. Scalable and Certifiable Graph Unlearning: Overcoming the Approximation Error Barrier
  18. TGB-Seq Benchmark: Challenging Temporal GNNs with Complex Sequential Dynamics
  19. TIDFormer: Exploiting Temporal and Interactive Dynamics Makes A Great Dynamic Graph Transformer
  20. Towards Effective and Efficient Continual Pre-training of Large Language Models
  21. Beyond Over-smoothing: Uncovering the Trainability Challenges in Deep Graph Neural Networks
  22. EquiPocket: an E(3)-Equivariant Geometric Graph Neural Network for Ligand Binding Site Prediction
  23. Exploring Neural Scaling Law and Data Pruning Methods For Node Classification on Large-scale Graphs
  24. Federated Heterogeneous Contrastive Distillation for Molecular Representation Learning
  25. Intruding with Words: Towards Understanding Graph Injection Attacks at the Text Level
  26. Learning-based Property Estimation with Polynomials
  27. Optimal Matrix Sketching over Sliding Windows
  28. PRICE: A Pretrained Model for Cross-Database Cardinality Estimation
  29. PolyFormer: Scalable Node-wise Filters via Polynomial Graph Transformer
  30. PolyGCL: GRAPH CONTRASTIVE LEARNING via Learnable Spectral Polynomial Filters
  31. S-MolSearch: 3D Semi-supervised Contrastive Learning for Bioactive Molecule Search
  32. SRAP-Agent: Simulating and Optimizing Scarce Resource Allocation Policy with LLM-based Agent
  33. Spectral Heterogeneous Graph Convolutions via Positive Noncommutative Polynomials