most citedMing-Omni: A Unified Multimodal Model for Perception and Generation

1 citations · 1 across the 4 of their papers we have counts for

collaborators

7 papers

cs.RO2026

Learning 4D Geometric Priors for Inference-Efficient World Action Models

Jianjun Zhang, Jian Zhu, Taiyi Su +4

World Action Models (WAMs) have shown strong potential for robotic manipulation by jointly modeling visual future dynamics and executable action sequences. However, existing video-…

cs.RO2026

PiL-World: A Chunk-Wise World Model for VLA Policy-in-the-Loop Evaluation

Chong Ma, Taiyi Su, Jian Zhu +4

Vision-language-action (VLA) policies operate in a closed loop in real-world robot tasks: a robot observes the scene, executes an action chunk, and conditions its next decision on…

cs.RO2025

Towards High-Consistency Embodied World Model with Multi-View Trajectory Videos

Taiyi Su, Jian Zhu, Yaxuan Li +5

Embodied world models aim to predict and interact with the physical world through visual observations and actions. However, existing models struggle to accurately translate low-lev…

cs.CV2025

Ming-Flash-Omni: A Sparse, Unified Architecture for Multimodal Perception and Generation

Inclusion AI, :, Bowen Ma +73

We propose Ming-Flash-Omni, an upgraded version of Ming-Omni, built upon a sparser Mixture-of-Experts (MoE) variant of Ling-Flash-2.0 with 100 billion total parameters, of which on…

cs.CV2025

MagicRoad: Semantic-Aware 3D Road Surface Reconstruction via Obstacle Inpainting

Xingyue Peng, Yuandong Lyu, Lang Zhang +8

Road surface reconstruction is essential for autonomous driving, supporting centimeter-accurate lane perception and high-definition mapping in complex urban environments.While rece…

cs.AI20251 cited

Ming-Omni: A Unified Multimodal Model for Perception and Generation

Inclusion AI, Biao Gong, Cheng Zou +55

We propose Ming-Omni, a unified multimodal model capable of processing images, text, audio, and video, while demonstrating strong proficiency in both speech and image generation. M…