6 papers
Multimodal Chain of Continuous Thought for Latent-Space Reasoning in Vision-Language Models
Tan-Hanh Pham, Chris Ngo
Many reasoning techniques for large multimodal models adapt language model approaches, such as Chain-of-Thought (CoT) prompting, which express reasoning as word sequences. While ef…
A Novel Framework for Automated Explain Vision Model Using Vision-Language Models
Phu-Vinh Nguyen, Tan-Hanh Pham, Chris Ngo +1
The development of many vision models mainly focuses on improving their performance using metrics such as accuracy, IoU, and mAP, with less attention to explainability due to the c…
RARL: Improving Medical VLM Reasoning and Generalization with Reinforcement Learning and LoRA under Data and Hardware Constraints
Tan-Hanh Pham, Chris Ngo
The growing integration of vision-language models (VLMs) in medical applications offers promising support for diagnostic reasoning. However, current medical VLMs often face limitat…
IQBench: How "Smart'' Are Vision-Language Models? A Study with Human IQ Tests
Tan-Hanh Pham, Phu-Vinh Nguyen, Dang The Hung +5
Although large Vision-Language Models (VLMs) have demonstrated remarkable performance in a wide range of multimodal tasks, their true reasoning capabilities on human IQ tests remai…
SilVar-Med: A Speech-Driven Visual Language Model for Explainable Abnormality Detection in Medical Imaging
Tan-Hanh Pham, Chris Ngo, Trong-Duong Bui +3
Medical Visual Language Models have shown great potential in various healthcare applications, including medical image captioning and diagnostic assistance. However, most existing m…
SilVar: Speech Driven Multimodal Model for Reasoning Visual Question Answering and Object Localization
Tan-Hanh Pham, Hoang-Nam Le, Phu-Vinh Nguyen +2
Visual Language Models have demonstrated remarkable capabilities across tasks, including visual question answering and image captioning. However, most models rely on text-based ins…