Large language models (LLMs) are a special class of pretrained language models (PLMs)
obtained by scaling model size, pretraining corpus and computation. LLMs, because of their …

In the past year, MultiModal Large Language Models (MM-LLMs) have undergone
substantial advancements, augmenting off-the-shelf LLMs to support MM inputs or outputs …

We present Video-LLaMA, a multi-modal framework that empowers Large Language Models
(LLMs) with the capability of understanding both visual and auditory content in the video …

While recently Multimodal Large Language Models (MM-LLMs) have made exciting strides,
they mostly fall prey to the limitation of only input-side multimodal understanding, without the …

Neural compression is the application of neural networks and other machine learning
methods to data compression. Recent advances in statistical machine learning have opened …

We present PandaGPT, an approach to emPower large lANguage moDels with visual and
Auditory instruction-following capabilities. Our pilot experiments show that PandaGPT can …

Within the vast expanse of computerized language processing, a revolutionary entity known
as Large Language Models (LLMs) has emerged, wielding immense power in its capacity to …

Thanks to the emerging of foundation models, the large language and vision models are
integrated to acquire the multimodal ability of visual captioning, question answering, etc …

Recently, large language models (LLMs) have shown great potential in recommender
systems, either improving existing recommendation models or serving as the backbone …

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