Despite significant progress in generative AI, comprehensive evaluation remains
challenging because of the lack of effective metrics and standardized benchmarks. For …

As large language models have demonstrated impressive performance in many domains,
recent works have adopted language models (LMs) as controllers of visual modules for …

Evaluating text-to-image models is notoriously difficult. A strong recent approach for
assessing text-image faithfulness is based on QG/A (question generation and answering) …

Vision-language datasets are vital for both text-to-image (T2I) and image-to-text (I2T)
research. However, current datasets lack descriptions with fine-grained detail that would …

We introduce VideoPrism, a general-purpose video encoder that tackles diverse video
understanding tasks with a single frozen model. We pretrain VideoPrism on a …

While text-to-visual models now produce photo-realistic images and videos they struggle
with compositional text prompts involving attributes relationships and higher-order …

Highlighting particularly relevant regions of an image can improve the performance of vision-
language models (VLMs) on various vision-language (VL) tasks by guiding the model to …

With the significant advancements of Large Language Models (LLMs) in the field of Natural
Language Processing (NLP), the development of image-text multimodal models has …

The objective of text-to-image (T2I) personalization is to customize a diffusion model to a
user-provided reference concept generating diverse images of the concept aligned with the …

Recent progress in large-scale pre-training has led to the development of advanced vision-
language models (VLMs) with remarkable proficiency in comprehending and generating …