With the emergence of Large Language Models (LLMs) and Vision Foundation Models
(VFMs), multimodal AI systems benefiting from large models have the potential to equally …

Multimodal large language models (MLLMs) have gained significant attention due to their
strong multimodal understanding capability. However existing works rely heavily on modality …

The ability to associate touch with other modalities has huge implications for humans and
computational systems. However multimodal learning with touch remains challenging due to …

Abstract Recent progress in Large Multimodal Models (LMM) has opened up great
possibilities for various applications in the field of human-machine interactions. However …

Abstract Multimodal Large Language Models (MLLMs) have excelled in 2D image-text
comprehension and image generation but their understanding of the 3D world is notably …

Sequential recommendation is to predict the next item of interest for a user, based on her/his
interaction history with previous items. In conventional sequential recommenders, a common …

Recently, Large Language Models (LLMs) and Multimodal Large Language Models
(MLLMs) have shown promise in instruction following and 2D image understanding. While …

With the rising tide of large language models (LLMs), there has been a growing interest in
developing general-purpose instruction-following models, eg, ChatGPT. To this end, we …

The remarkable progress of Multi-modal Large Language Models (MLLMs) has garnered
unparalleled attention, due to their superior performance in visual contexts. However, their …

Multimodal large language models (MLLMs) have demonstrated remarkable success in
vision and visual-language tasks within the natural image domain. Owing to the significant …