7 citations · 16 across the 58 of their papers we have counts for
62 papers
VGA-BenchV2: An Expanded Unified Benchmark and Multi-Model Framework for Evaluating Video Aesthetics and Generation Quality
Longteng Jiang, DanDan Zheng, Qianqian Qiao +7
We introduce VGA-BenchV2, an extended human-aligned benchmark and optimization framework for jointly evaluating and improving video generation quality and aesthetic value. Built up…
Object-Uni: A Unified Model for Object-Centric Spatial Understanding and Controllable Generation
Mining Tan, Yinuo Wang, Ziqi Zhou +6
Unified models for visual understanding and generation have made rapid progress, yet they still lack the ability to understand and manipulate the spatial states of object instances…
Fusion Anything: A Generalized Multimodal Foundation Model
Huizi Cui, Zongbo Han, Chenggong Ding +6
Making prediction with multimodal data is widely used in diverse scenarios. Existing multimodal fusion models, once deployed, can only handle predefined modalities (e.g., vision, t…
VideoGAIA: A Benchmark for General AI Assistants on Agentic Video Understanding
Fan Zhang, Guangming Yao, Jinyang Wu +6
Video understanding is a fundamental task for evaluating the capabilities of multimodal large language models (MLLMs). However, existing leading models have already achieved approx…
GroupVideo: Multi-Identity Customized Text-to-Video Generation
Xinyang Song, Libin Wang, Jianxin Sun +4
Current identity customized video generation methodologies are predominantly limited to single-identity scenarios, as the lack of explicit identity separation mechanisms often lead…
Selecting Samples on Graphs: A Unified Dataset Pruning Framework for Lossless Training Acceleration
Dongyue Wu, Zilin Guo, Xiaoyu Li +4
The rapid growth of modern training datasets has significantly increased computational cost, motivating dataset pruning~(DP) methods which retain only a subset of informative sampl…
MemDreamer: Decoupling Perception and Reasoning for Long Video Understanding via Hierarchical Graph Memory and Agentic Retrieval Mechanism
Cong Chen, Guo Gan, Kaixiang Ji +7
Current Vision-Language Models struggle with hours-long videos because processing full-length visual sequences induces prohibitive token explosion and attention dilution. To overco…
GraphPO: Graph-based Policy Optimization for Reasoning Models
Yuliang Zhan, Xinyu Tang, Jian Li +7
Reinforcement Learning with Verifiable Rewards (RLVR) has become a standard paradigm for enhancing the capability of large reasoning models. RLVR typically samples responses indepe…
SPRI: SVD-Partitioned Residual Initialization for Data-Constrained MoE Upcycling
Weiqiao Shan, Ruixiang Mao, Yuang Li +10
Mixture-of-Experts (MoE) models enable efficient scaling, but training them from scratch remains prohibitively expensive. MoE upcycling mitigates this cost by converting pretrained…
COMPASS: Grounding Composition-Intent Guidance in Unified Multimodal Models
Ziqi Zhou, Weize Quan, Mining Tan +6
Composition is a high-level visual intent that governs where subjects are placed and how a scene is organized, yet current unified multimodal models remain unreliable at fine-grain…
The Wittgensteinian Representation Hypothesis: Is Language the Attractor of Multimodal Convergence?
Zhaoyang Zhang, Run Shao, Dongyue Wu +4
Understanding why independently trained neural networks from different modalities converge toward shared representations, and where this convergence leads, remains an open question…
VGA-Bench: A Unified Benchmark and Multi-Model Framework for Video Aesthetics and Generation Quality Evaluation
Longteng Jiang, DanDan Zheng, Qianqian Qiao +7
The rapid advancement of AIGC-based video generation has underscored the critical need for comprehensive evaluation frameworks that go beyond traditional generation quality metrics…
Dual Tuning for Reasoning Efficacy-Driven Data Curation in Multimodal LLM Training
Ruobing Zheng, Tianqi Li, Jianing Li +3
Reasoning post-training improves Large Language Models (LLMs) on complex tasks such as mathematics and coding, but its benefits across diverse multimodal tasks remains uncertain. T…
TriC-Motion: Tri-Domain Causal Modeling Grounded Text-to-Motion Generation
Yiyang Cao, Yunze Deng, Ziyu Lin +5
Text-to-motion generation, a rapidly evolving field in computer vision, aims to produce realistic and text-aligned motion sequences. Current methods primarily focus on spatial-temp…
GO-MLVTON: Garment Occlusion-Aware Multi-Layer Virtual Try-On with Diffusion Models
Yang Yu, Yunze Deng, Yige Zhang +8
Existing image-based virtual try-on (VTON) methods primarily focus on single-layer or multi-garment VTON, neglecting multi-layer VTON (ML-VTON), which involves dressing multiple la…
3SGen: Unified Subject, Style, and Structure-Driven Image Generation with Adaptive Task-specific Memory
Xinyang Song, Libin Wang, Weining Wang +6
Recent image generation approaches often address subject, style, and structure-driven conditioning in isolation, leading to feature entanglement and limited task transferability. I…
VADB: A Large-Scale Video Aesthetic Database with Professional and Multi-Dimensional Annotations
Qianqian Qiao, DanDan Zheng, Yihang Bo +7
Video aesthetic assessment, a vital area in multimedia computing, integrates computer vision with human cognition. Its progress is limited by the lack of standardized datasets and…
Ming-UniAudio: Speech LLM for Joint Understanding, Generation and Editing with Unified Representation
Canxiang Yan, Chunxiang Jin, Dawei Huang +22
Existing speech models suffer from competing requirements on token representations by understanding and generation tasks. This discrepancy in representation prevents speech languag…
PruneHal: Reducing Hallucinations in Multi-modal Large Language Models through Adaptive KV Cache Pruning
Fengyuan Sun, Hui Chen, Xinhao Xu +5
While multi-modal large language models (MLLMs) have made significant progress in recent years, the issue of hallucinations remains a major challenge. To mitigate this phenomenon,…
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…
ARGenSeg: Image Segmentation with Autoregressive Image Generation Model
Xiaolong Wang, Lixiang Ru, Ziyuan Huang +4
We propose a novel AutoRegressive Generation-based paradigm for image Segmentation (ARGenSeg), achieving multimodal understanding and pixel-level perception within a unified framew…
UniAlignment: Semantic Alignment for Unified Image Generation, Understanding, Manipulation and Perception
Xinyang Song, Libin Wang, Weining Wang +5
The remarkable success of diffusion models in text-to-image generation has sparked growing interest in expanding their capabilities to a variety of multi-modal tasks, including ima…
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…