5 papers
Cosmos 3: Omnimodal World Models for Physical AI
NVIDIA, :, Aditi +293
We introduce Cosmos 3, a family of omnimodal world models designed to jointly process and generate language, image, video, audio, and action sequences within a unified mixture-of-t…
Alpamayo-R1: Bridging Reasoning and Action Prediction for Generalizable Autonomous Driving in the Long Tail
NVIDIA, :, Yan Wang +41
End-to-end architectures trained via imitation learning have advanced autonomous driving by scaling model size and data, yet performance remains brittle in safety-critical long-tai…
Hallucination of Multimodal Large Language Models: A Survey
Zechen Bai, Pichao Wang, Tianjun Xiao +4
This survey presents a comprehensive analysis of the phenomenon of hallucination in multimodal large language models (MLLMs), also known as Large Vision-Language Models (LVLMs), wh…
Bridging Information Asymmetry in Text-video Retrieval: A Data-centric Approach
Zechen Bai, Tianjun Xiao, Tong He +4
As online video content rapidly grows, the task of text-video retrieval (TVR) becomes increasingly important. A key challenge in TVR is the information asymmetry between video and…
Rethinking The Training And Evaluation of Rich-Context Layout-to-Image Generation
Jiaxin Cheng, Zixu Zhao, Tong He +3
Recent advancements in generative models have significantly enhanced their capacity for image generation, enabling a wide range of applications such as image editing, completion an…