3 papers
cs.CV2025
ChartQA-X: Generating Explanations for Visual Chart Reasoning
Shamanthak Hegde, Pooyan Fazli, Hasti Seifi
The ability to explain complex information from chart images is vital for effective data-driven decision-making. In this work, we address the challenge of generating detailed expla…
cs.CV2025
Dual Caption Preference Optimization for Diffusion Models
Amir Saeidi, Yiran Luo, Agneet Chatterjee +4
Recent advancements in human preference optimization, originally developed for Large Language Models (LLMs), have shown significant potential in improving text-to-image diffusion m…
cs.CV2023
Making the V in Text-VQA Matter
Shamanthak Hegde, Soumya Jahagirdar, Shankar Gangisetty
Text-based VQA aims at answering questions by reading the text present in the images. It requires a large amount of scene-text relationship understanding compared to the VQA task.…