Abstract Large Vision-Language Models (LVLMs) have advanced considerably intertwining
visual recognition and language understanding to generate content that is not only coherent …

Large vision-language models (LVLMs) have shown remarkable abilities in understanding
visual information with human languages. However, LVLMs still suffer from object …

While GPT-4V (ision) impressively models both visual and textual information
simultaneously, it's hallucination behavior has not been systematically assessed. To bridge …

The advent of large vision-language models (LVLMs) represents a remarkable advance in
the quest for artificial general intelligence. However, the models' effectiveness in both …

We address the challenge of generating fair and unbiased image retrieval results given
neutral textual queries (with no explicit gender or race connotations), while maintaining the …

Noisy correspondence that refers to mismatches in cross-modal data pairs is prevalent on
human-annotated or web-crawled datasets. Prior approaches to leverage such data mainly …

In the realms of computer vision and natural language processing, Large Vision-Language
Models (LVLMs) have become indispensable tools, proficient in generating textual …

Food computing has emerged as a prominent multidisciplinary field of research in recent
years. An ambitious goal of food computing is to develop end-to-end intelligent systems …

Despite the astonishing performance of recent Large Vision-Language Models (LVLMs),
these models often generate inaccurate responses. To address this issue, previous studies …

This paper studies the problem of semi-supervised 2D-3D retrieval which aims to align both
labeled and unlabeled 2D and 3D data into the same embedding space. The problem is …