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cs.CV2026

FedOT: Ownership Verification and Leakage Tracing via Watermarks for Federated LDMs

Wenlong Cheng, Yuan Gan, Yunqiu Xu +1

Training Latent Diffusion Models (LDMs) within Federated Learning (FL) has attracted increasing attention due to its ability to combine the powerful generative capacity of LDMs wit…

cs.CV2026

From 2D Grids to 1D Tokens: Reforming Shared Representations for Multimodal Image Fusion

Yuchen Xian, Yunqiu Xu, Yang He +1

Multimodal image fusion aims to integrate complementary information from different modalities into a fused image that preserves rich local details while maintaining globally consis…

cs.CV2026

Echoes of ownership: Adversarial-guided dual injection for copyright protection in MLLMs

Chengwei Xia, Fan Ma, Ruijie Quan +3

With the rapid deployment of multimodal large language models (MLLMs), disputes regarding model ownership have become increasingly frequent, raising significant concerns about inte…

cs.CV2026

CogFlow: Bridging Perception and Reasoning through Knowledge Internalization for Visual Mathematical Problem Solving

Shuhang Chen, Yunqiu Xu, Junjie Xie +7

Despite significant progress, multimodal large language models continue to struggle with visual mathematical problem solving. Some recent works recognize that visual perception is…

cs.CV2025

BideDPO: Conditional Image Generation with Simultaneous Text and Condition Alignment

Dewei Zhou, Mingwei Li, Zongxin Yang +5

Conditional image generation enhances text-to-image synthesis with structural, spatial, or stylistic priors, but current methods face challenges in handling conflicts between sourc…

cs.CV2025

MathFlow: Enhancing the Perceptual Flow of MLLMs for Visual Mathematical Problems

Shuhang Chen, Hangjie Yuan, Yunqiu Xu +5

Despite strong results on many tasks, multimodal large language models (MLLMs) still underperform on visual mathematical problem solving, especially in reliably perceiving and inte…