We introduce InternVideo2, a new family of video foundation models (ViFM) that achieve the
state-of-the-art results in video recognition, video-text tasks, and video-centric dialogue. Our …

With the development of artificial intelligence and breakthroughs in deep learning, large-
scale foundation models (FMs), such as generative pre-trained transformer (GPT), Sora, etc …

World models are progressively being employed across diverse fields, extending from basic
environment simulation to complex scenario construction. However, existing models are …

Video generation requires modeling a vast spatiotemporal space, which demands
significant computational resources and data usage. To reduce the complexity, the …

We introduce Diffusion Policy Policy Optimization, DPPO, an algorithmic framework
including best practices for fine-tuning diffusion-based policies (eg Diffusion Policy) in …

We present GameNGen, the first game engine powered entirely by a neural model that
enables real-time interaction with a complex environment over long trajectories at high …

We introduce Latent Action Pretraining for general Action models (LAPA), an unsupervised
method for pretraining Vision-Language-Action (VLA) models without ground-truth robot …

Artificial intelligence (AI) has rapidly developed through advancements in computational
power and the growth of massive datasets. However, this progress has also heightened …

In-context learning (ICL) is the ability of a model to learn a new task by observing a few
exemplars in its context. While prevalent in NLP, this capability has recently also been …

We show that, simply initializing image understanding models using a pre-trained UNet (or
transformer) of diffusion models, it is possible to achieve remarkable transferable …