In recent years, foundation models (FMs) such as large language models (LLMs) and latent
diffusion models (LDMs) have profoundly impacted diverse sectors, including music. This …

We present ControlLLM, a novel framework that enables large language models (LLMs) to
utilize multi-modal tools for solving complex real-world tasks. Despite the remarkable …

In this work, we systematically study music generation conditioned solely on the video. First,
we present a large-scale dataset comprising 360K video-music pairs, including various …

The rapid development of large language models (LLMs) has been witnessed in recent
years. Based on the powerful LLMs, multi-modal LLMs (MLLMs) extend the modality from …

Image editing involves a variety of complex tasks and requires efficient and precise
manipulation techniques. In this paper, we present MagicQuill, an integrated image editing …

Multimodal Large Models (MLMs) are becoming a significant research focus, combining
powerful large language models with multimodal learning to perform complex tasks across …

Massive multi-modality datasets play a significant role in facilitating the success of large
video-language models. However, current video-language datasets primarily provide text …

World models integrate raw data from various modalities, such as images and language to
simulate comprehensive interactions in the world, thereby displaying crucial roles in fields …

We present TALE, a novel training-free framework harnessing the generative capabilities of
text-to-image diffusion models to address the cross-domain image composition task that …

The exploration of various vision-language tasks, such as visual captioning, visual question
answering, and visual commonsense reasoning, is an important area in artificial intelligence …