6 papers
Dr. Seg: Revisiting GRPO Training for Visual Large Language Models through Perception-Oriented Design
Haoxiang Sun, Tao Wang, Chenwei Tang +2
Following the success of Group Relative Policy Optimization (GRPO) in foundation LLMs, an increasing number of works have sought to adapt GRPO to Visual Large Language Models (VLLM…
Adaptive Image Zoom-in with Bounding Box Transformation for UAV Object Detection
Tao Wang, Chenyu Lin, Chenwei Tang +5
Detecting objects from UAV-captured images is challenging due to the small object size. In this work, a simple and efficient adaptive zoom-in framework is explored for object detec…
Multimodal Information Fusion for Chart Understanding: A Survey of MLLMs -- Evolution, Limitations, and Cognitive Enhancement
Zhihang Yi, Jian Zhao, Jiancheng Lv +1
Chart understanding is a quintessential information fusion task, requiring the seamless integration of graphical and textual data to extract meaning. The advent of Multimodal Large…
Dual Prompt Learning for Adapting Vision-Language Models to Downstream Image-Text Retrieval
Yifan Wang, Tao Wang, Chenwei Tang +5
Recently, prompt learning has demonstrated remarkable success in adapting pre-trained Vision-Language Models (VLMs) to various downstream tasks such as image classification. Howeve…
Precision Neural Network Quantization via Learnable Adaptive Modules
Wenqiang Zhou, Zhendong Yu, Xinyu Liu +5
Quantization Aware Training (QAT) is a neural network quantization technique that compresses model size and improves operational efficiency while effectively maintaining model perf…
Memory-Augmented Dual-Decoder Networks for Multi-Class Unsupervised Anomaly Detection
Jingyu Xing, Chenwei Tang, Tao Wang +5
Recent advances in unsupervised anomaly detection (UAD) have shifted from single-class to multi-class scenarios. In such complex contexts, the increasing pattern diversity has brou…