3 papers
cs.CV2026
HiRes-LLaVA: Restoring Fragmentation Input in High-Resolution Large Vision-Language Models
Runhui Huang, Xinpeng Ding, Chunwei Wang +7
High-resolution inputs enable Large Vision-Language Models (LVLMs) to discern finer visual details, enhancing their comprehension capabilities. To reduce the training and computati…
cs.CV2025
Getting More Juice Out of Your Data: Hard Pair Refinement Enhances Visual-Language Models Without Extra Data
Haonan Wang, Minbin Huang, Runhui Huang +7
Contrastive Language-Image Pre-training (CLIP) has become the standard for cross-modal image-text representation learning. Improving CLIP typically requires additional data and ret…
cs.CV2024
RealignDiff: Boosting Text-to-Image Diffusion Model with Coarse-to-fine Semantic Re-alignment
Zutao Jiang, Guian Fang, Jianhua Han +5
Recent advances in text-to-image diffusion models have achieved remarkable success in generating high-quality, realistic images from textual descriptions. However, these approaches…