6 papers
CountEx: Fine-Grained Counting via Exemplars and Exclusion
Yifeng Huang, Gia Khanh Nguyen, Minh Hoai
This paper presents CountEx, a discriminative visual counting framework designed to address a key limitation of existing prompt-based methods: the inability to explicitly exclude v…
WearVQA: A Visual Question Answering Benchmark for Wearables in Egocentric Authentic Real-world scenarios
Eun Chang, Zhuangqun Huang, Yiwei Liao +19
We introduce WearVQA, the first benchmark specifically designed to evaluate the Visual Question Answering (VQA) capabilities of multi-model AI assistant on wearable devices like sm…
Improving Human Verification of LLM Reasoning through Interactive Explanation Interfaces
Runtao Zhou, Giang Nguyen, Nikita Kharya +2
The reasoning capabilities of Large Language Models (LLMs) have led to their increasing employment in several critical applications, particularly education, where they support prob…
Can Current AI Models Count What We Mean, Not What They See? A Benchmark and Systematic Evaluation
Gia Khanh Nguyen, Yifeng Huang, Minh Hoai
Visual counting is a fundamental yet challenging task, especially when users need to count objects of a specific type in complex scenes. While recent models, including class-agnost…
ViQA-COVID: COVID-19 Machine Reading Comprehension Dataset for Vietnamese
Hai-Chung Nguyen-Phung, Ngoc C. Lê, Van-Chien Nguyen +2
After two years of appearance, COVID-19 has negatively affected people and normal life around the world. As in May 2022, there are more than 522 million cases and six million death…
Crowdsource, Crawl, or Generate? Creating SEA-VL, a Multicultural Vision-Language Dataset for Southeast Asia
Samuel Cahyawijaya, Holy Lovenia, Joel Ruben Antony Moniz +89
Southeast Asia (SEA) is a region of extraordinary linguistic and cultural diversity, yet it remains significantly underrepresented in vision-language (VL) research. This often resu…