PPaperPicks

Lingqiao Liu

22 papers at tracked venues · 10 at CORE A* · active 20242026

Venues

Frequent coauthors

Papers

  1. HiTVideo: Hierarchical Tokenizers for Enhancing Text-to-Video Generation with Autoregressive Large Language Models
  2. MoSCo: Real-time and Efficient Text-to-Motion Synthesis via Delta Training
  3. ReFINE: A Reward-Based Framework for Interpretable and Nuanced Evaluation of Radiology Report Generation
  4. Revisiting Vision-Language Foundations for No-Reference Image Quality Assessment
  5. A Simple-but-Effective Baseline for Training-Free Class-Agnostic Counting
  6. Attention-Driven GUI Grounding: Leveraging Pretrained Multimodal Large Language Models Without Fine-Tuning
  7. Chain-of-Action: Trajectory Autoregressive Modeling for Robotic Manipulation
  8. Effective Tuning Strategies for Generalist Robot Manipulation Policies
  9. Efficiently Selecting Response Generation Strategies for Synthetic Data Construction by Self-Aligned Perplexity
  10. Embodied Domain Adaptation for Object Detection
  11. Enhancing Close-up Novel View Synthesis via Pseudo-labeling
  12. Let Your Video Listen to Your Music! - Beat-Aligned, Content-Preserving Video Editing with Arbitrary Music
  13. One Last Attention for Your Vision-Language Model
  14. PedCLIP: A Vision-Language Model for Pediatric X-Rays with Mixture of Body Part Experts
  15. Decomposing Disease Descriptions for Enhanced Pathology Detection: A Multi-Aspect Vision-Language Pre-Training Framework
  16. I Learn Better If You Speak My Language: Understanding the Superior Performance of Fine-Tuning Large Language Models with LLM-Generated Responses
  17. Improving Online Source-Free Domain Adaptation for Object Detection by Unsupervised Data Acquisition
  18. KARGEN: Knowledge-Enhanced Automated Radiology Report Generation Using Large Language Models
  19. LFME: A Simple Framework for Learning from Multiple Experts in Domain Generalization
  20. MRScore: Evaluating Medical Report with LLM-Based Reward System
  21. On Learning Discriminative Features from Synthesized Data for Self-supervised Fine-Grained Visual Recognition
  22. Unlocking the Potential of Pre-Trained Vision Transformers for Few-Shot Semantic Segmentation through Relationship Descriptors