The advent of vision-language pre-training techniques enhanced substantial progress in the
development of models for image captioning. However, these models frequently produce …

The advent of vision-language pre-training techniques enhanced substantial progress in the
development of models for image captioning. However, these models frequently produce …

Abstract Perceptually Aligned Gradients (PAG) refer to an intriguing property observed in
robust image classification models, wherein their input gradients align with human …

The ability to recognize and reason about text embedded in visual inputs is often lacking in
vision-and-language (V&L) models, perhaps because V&L pre-training methods have often …

Abstract We propose Strongly Supervised pre-training with ScreenShots (S4)-a novel pre-
training paradigm for Vision-Language Models using data from large-scale web screenshot …

Vision-Language (VL) models have gained significant research focus enabling remarkable
advances in multimodal reasoning. These architectures typically comprise a vision encoder …

The increasing use of transformer-based large language models brings forward the
challenge of processing long sequences. In document visual question answering (DocVQA) …

In recent years, notable advancements have been made in the domain of visual document
understanding, with the prevailing architecture comprising a cascade of vision and language …

Extracting text from an image using a Visual Question Answering (VQA) system is an
application at the intersection of computer vision and Natural Language Processing (NLP) to …

Understanding visual question-answering (VQA) will be essential for many human tasks.
However, it poses significant obstacles at the core of artificial intelligence as a multimodal …