activity
20232026
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

6 papers

cs.AI2026

Auto-Rubric as Reward: From Implicit Preferences to Explicit Multimodal Generative Criteria

Juanxi Tian, Fengyuan Liu, Jiaming Han +6

Aligning multimodal generative models with human preferences demands reward signals that respect the compositional, multi-dimensional structure of human judgment. Prevailing RLHF a…

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.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…

cs.CV2024

M2-Encoder: Advancing Bilingual Image-Text Understanding by Large-scale Efficient Pretraining

Qingpei Guo, Furong Xu, Hanxiao Zhang +6

Vision-language foundation models like CLIP have revolutionized the field of artificial intelligence. Nevertheless, VLM models supporting multi-language, e.g., in both Chinese and…

cs.CV2024

SyCoCa: Symmetrizing Contrastive Captioners with Attentive Masking for Multimodal Alignment

Ziping Ma, Furong Xu, Jian Liu +2

Multimodal alignment between language and vision is the fundamental topic in current vision-language model research. Contrastive Captioners (CoCa), as a representative method, inte…

cs.CV2023

Text as Image: Learning Transferable Adapter for Multi-Label Classification

Xuelin Zhu, Jiuxin Cao, Jian liu +7

Pre-trained vision-language models have notably accelerated progress of open-world concept recognition. Their impressive zero-shot ability has recently been transferred to multi-la…