PPaperPicks

Yue Cui

Hong Kong University of Science and Technology, SAR, China

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

Venues

Frequent coauthors

Papers

  1. ACR: Adaptive Context Refactoring via Context Refactoring Operators for Multi-Turn Dialogue
  2. Active Multi-source Domain Adaptation for Multimodal Fake News Detection
  3. Branch-and-Browse: Efficient and Controllable Web Exploration with Tree-Structured Reasoning and Action Memory
  4. KCVR: Knowledge-Centric Video Reconstruction for Structured Pedagogical Summarization via Dynamic Graph Planning
  5. RSDA: Restoring Stale Data Affinity via Dynamic Renovation Strategy for Mitigating Data Scarcity
  6. ReTRE: Benchmarking LLM Transfer Robustness with Structure-Preserving Variants
  7. ST-LEGO: Large Language Models as Modular Architects for Traffic Prediction
  8. TIV: Thought Injection via Vectors for Efficient Reasoning in Large Reasoning Models
  9. TacpAgent: Enhancing Student Engagement in Classroom Exercises Through LLM-Generated Feedback
  10. A Bargaining-Based Approach for Feature Trading in Vertical Federated Learning
    ICDE 2025 · Yue Cui
  11. Consistent and Invariant Generalization Learning for Short-video Misinformation Detection
  12. DIDS: Domain Impact-aware Data Sampling for Large Language Model Training
  13. Enhancing Tool Learning in Large Language Models with Hierarchical Error Checklists
    ACL 2025 · Yue Cui
  14. Fine-Grained Traffic Inference from Road to Lane via Spatio-Temporal Graph Node Generation
  15. Semantic-guided Diverse Decoding for Large Language Model
  16. FRESH: Towards Efficient Graph Queries in an Outsourced Graph
  17. Multi-Agent Based Casual Triple Extraction For Factuality Evaluation Using Large Language Models
  18. ST-ABC: Spatio-Temporal Attention-Based Convolutional Network for Multi-Scale Lane-Level Traffic Prediction
  19. Seeing the Forest for the Trees: Road-Level Insights Assisted Lane-Level Traffic Prediction
  20. Task Recommendation in Spatial Crowdsourcing: A Trade-Off Between Diversity and Coverage