4 papers
VESTA: Visual Exploration with Statistical Tool Agents
William Rudman, Abhishek Divekar, Kanishk Jain +6
Fitting quantitative models to data is a central step in scientific workflows, yet it remains one of the least automated. Recent agent-based systems leverage language and vision-la…
Learning What Matters: Prioritized Concept Learning via Relative Error-driven Sample Selection
Shivam Chandhok, Qian Yang, Oscar Manas +3
Instruction tuning has been central to the success of recent vision-language models (VLMs), but it remains expensive-requiring large-scale datasets, high-quality annotations, and l…
DRISHTIKON: A Multimodal Multilingual Benchmark for Testing Language Models' Understanding on Indian Culture
Arijit Maji, Raghvendra Kumar, Akash Ghosh +6
We introduce DRISHTIKON, a first-of-its-kind multimodal and multilingual benchmark centered exclusively on Indian culture, designed to evaluate the cultural understanding of genera…
Benchmarking Vision Language Models for Cultural Understanding
Shravan Nayak, Kanishk Jain, Rabiul Awal +5
Foundation models and vision-language pre-training have notably advanced Vision Language Models (VLMs), enabling multimodal processing of visual and linguistic data. However, their…