Large language models (LLMs) have demonstrated excellent zero-shot generalization to
new language tasks. However, effective utilization of LLMs for zero-shot visual question …

Visual Question Answering (VQA) has benefited from increasingly sophisticated models, but
has not enjoyed the same level of engagement in terms of data creation. In this paper, we …

Large language models (LLMs) have demonstrated excellent zero-shot generalization to
new language tasks. However, effective utilization of LLMs for zero-shot visual question …

Image captioning means generate descriptive sentences from a query image automatically.
It has recently received widespread attention from the computer vision and natural language …

Few images on the Web receive alt-text descriptions that would make them accessible to
blind and low vision (BLV) users. Image-based NLG systems have progressed to the point …

Visual Question Answering (VQA) has been primarily studied through the lens of the English
language. Yet, tackling VQA in other languages in the same manner would require a …

This paper studies a category of visual question answering tasks, in which accessing
external knowledge is necessary for answering the questions. This category is called …

Due to the prominent zero-shot generalization in new language tasks shown by large
language models (LLMs), applying LLMs for zero-shot visual question answering (VQA) has …

Referenceless metrics (eg, CLIPScore) use pretrained vision--language models to assess
image descriptions directly without costly ground-truth reference texts. Such methods can …

In text summarization and simplification, system outputs must be evaluated along multiple
dimensions such as relevance, factual consistency, fluency, and grammaticality, and a wide …