Large language models (LLMs) have demonstrated remarkable language abilities. GPT-4,
based on advanced LLMs, exhibits extraordinary multimodal capabilities beyond previous …

Recently, several methods have been proposed to augment large Vision Language Models
(VLMs) for Visual Question Answering (VQA) simplicity by incorporating external knowledge …

Despite the significant success of large vision-language models (LVLMs), some studies
have revealed that LVLMs suffer from the hallucination problem, where the LVLMs' response …

Image-grounded dialogue systems benefit greatly from integrating visual information,
resulting in high-quality response generation. However, current models struggle to …

Visual information is central to conversation: body gestures and physical behaviour, for
example, contribute to meaning that transcends words alone. To date, however, most neural …

With the ability to collect vast amounts of image and natural language data from the web,
there has been a remarkable advancement in Large-scale Language Models (LLMs). This …

Abstract Knowledge-based Visual Dialog is a challenging vision-language task, where an
agent engages in dialog to answer questions with humans based on the input image and …

Given a query from one modality, few-shot cross-modal retrieval (CMR) retrieves
semantically similar instances in another modality with the target domain including classes …

Code-switching entails mixing multiple languages. It is an increasingly occurring
phenomenon in social media texts. Usually, code-mixed texts are written in a single script …

Visual Dialog (VD) is a task where an agent answers a series of image-related questions
based on a multi-round dialog history. However, previous VD methods often treat the entire …