2 citations · 3 across the 10 of their papers we have counts for
10 papers
Affective Flow Language Model for Emotional Support Conversation
Chenghui Zou, Ning Wang, Tiesunlong Shen +5
Large language models (LLMs) have advanced emotional support conversation, but existing alignment methods rely mainly on sparse preferences at the response level or outcomes at the…
Ming-UniVision: Joint Image Understanding and Generation with a Unified Continuous Tokenizer
Ziyuan Huang, DanDan Zheng, Cheng Zou +13
Visual tokenization remains a core challenge in unifying visual understanding and generation within the autoregressive paradigm. Existing methods typically employ tokenizers in dis…
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…
GUI-Shepherd: Reliable Process Reward and Verification for Long-Sequence GUI Tasks
Cong Chen, Kaixiang Ji, Hao Zhong +9
Autonomous agents for long-sequence Graphical User Interface tasks are hindered by sparse rewards and the intractable credit assignment problem. To address these challenges, we int…
HieraTok: Multi-Scale Visual Tokenizer Improves Image Reconstruction and Generation
Cong Chen, Ziyuan Huang, Cheng Zou +6
In this work, we present HieraTok, a novel multi-scale Vision Transformer (ViT)-based tokenizer that overcomes the inherent limitation of modeling single-scale representations. Thi…
Video Virtual Try-on with Conditional Diffusion Transformer Inpainter
Cheng Zou, Senlin Cheng, Bolei Xu +4
Video virtual try-on aims to naturally fit a garment to a target person in consecutive video frames. It is a challenging task, on the one hand, the output video should be in good s…
Ming-Lite-Uni: Advancements in Unified Architecture for Natural Multimodal Interaction
Inclusion AI, Biao Gong, Cheng Zou +14
We introduce Ming-Lite-Uni, an open-source multimodal framework featuring a newly designed unified visual generator and a native multimodal autoregressive model tailored for unifyi…
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…
ACTIVE-o3: Empowering MLLMs with Active Perception via Pure Reinforcement Learning
Muzhi Zhu, Hao Zhong, Canyu Zhao +9
Active vision, also known as active perception, refers to actively selecting where and how to look in order to gather task-relevant information. It is a critical component of effic…
DynaMath: A Dynamic Visual Benchmark for Evaluating Mathematical Reasoning Robustness of Vision Language Models
Chengke Zou, Xingang Guo, Rui Yang +3
The rapid advancements in Vision-Language Models (VLMs) have shown great potential in tackling mathematical reasoning tasks that involve visual context. Unlike humans who can relia…