activity
20242026
most citedMing-Omni: A Unified Multimodal Model for Perception and Generation

1 citations · 1 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2026

KTV: Keyframes and Key Tokens Selection for Efficient Training-Free Video LLMs

Baiyang Song, Jun Peng, Yuxin Zhang +3

Training-free video understanding leverages the strong image comprehension capabilities of pre-trained vision language models (VLMs) by treating a video as a sequence of static fra…

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.AI2025★ 1 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…

cs.CV2025

Multimodal Representation Learning Techniques for Comprehensive Facial State Analysis

Kaiwen Zheng, Xuri Ge, Junchen Fu +2

Multimodal foundation models have significantly improved feature representation by integrating information from multiple modalities, making them highly suitable for a broader set o…

cs.CV2024

Efficient Event Stream Super-Resolution with Recursive Multi-Branch Fusion

Quanmin Liang, Zhilin Huang, Xiawu Zheng +4

Current Event Stream Super-Resolution (ESR) methods overlook the redundant and complementary information present in positive and negative events within the event stream, employing…