Large language models (LLMs) are gaining increasing popularity in both academia and
industry, owing to their unprecedented performance in various applications. As LLMs …

Since its inception in 2015, the YOLO (You Only Look Once) variant of object detectors has
rapidly grown, with the latest release of YOLO-v8 in January 2023. YOLO variants are …

Designing computationally efficient network architectures remains an ongoing necessity in
computer vision. In this paper, we adapt Mamba, a state-space language model, into …

The recent breakthroughs in natural language processing for model pretraining on large
quantities of data have opened the way for similar foundation models in computer vision …

We present SDXL, a latent diffusion model for text-to-image synthesis. Compared to
previous versions of Stable Diffusion, SDXL leverages a three times larger UNet backbone …

Large language models (LLMs) are increasingly deployed as the backend for various
applications, including code completion tools and AI-powered search engines. Unlike …

As the core building block of vision transformers, attention is a powerful tool to capture long-
range dependency. However, such power comes at a cost: it incurs a huge computation …

We propose a simple pairwise sigmoid loss for image-text pre-training. Unlike standard
contrastive learning with softmax normalization, the sigmoid loss operates solely on image …

Quantitative evaluation of tissue images is crucial for computational pathology (CPath) tasks,
requiring the objective characterization of histopathological entities from whole-slide images …

The recent success of text-to-image synthesis has taken the world by storm and captured the
general public's imagination. From a technical standpoint, it also marked a drastic change in …