Image degradation from blur, noise, compression, and poor illumination severely undermines multimodal understanding in real-world settings. Unified multimodal models that combine understanding and generation within a single architecture are a natural fit for this challenge, as their generative pathway can model the fine-grained visual structure that degradation destroys. Yet these models fail to leverage their own generative capacity on degraded inputs. We trace this disconnect to two compounding factors: existing training regimes never ask the model to invoke generation during reasoning, and the standard decode-reencode pathway does not support effective joint optimization. We present CLEAR, a framework that connects the two capabilities through three progressive steps: (1) supervised fine-tuning on a degradation-aware dataset to establish the generate-then-answer reasoning pattern; (2) a Latent Representation Bridge that replaces the decode-reencode detour with a direct, optimizable connection between generation and reasoning; (3) Interleaved GRPO, a reinforcement learning method that jointly optimizes text reasoning and visual generation under answer-correctness rewards. We construct MMD-Bench, covering three degradation severity levels across six standard multimodal benchmarks. Experiments show that CLEAR substantially improves robustness on degraded inputs while preserving clean-image performance. Our analysis further reveals that removing pixel-level reconstruction supervision leads to intermediate visual states with higher perceptual quality, suggesting that task-driven optimization and visual quality are naturally aligned.
Real-World Scene Recovery for Scattering-Degraded Images Using Spatial and Frequency Priors
College of Artificial Intelligence, Southwest University（西南大学人工智能学院）；School of Biomedical Engineering, Shenzhen University Medical School, Shenzhen University（深圳大学医学院生物医学工程学院）；School of Cyber Science and Technology, Shenzhen Campus, Sun Yat-sen University（中山大学深圳校区计算机科学与技术学院）；ETcTI, University Politehnica Timisoara（蒂森堡大学ETcTI学院）；College of Computing and Data Science, Nanyang Technological University (NTU)（南洋理工大学计算机与数据科学学院）
TTTIR: Unlocking Instance-Specific State Evolution via Test-Time Training for Image Restoration
Harbin Institute of Technology, Shenzhen（哈尔滨工业大学（深圳））；Tsinghua University（清华大学）；École Polytechnique Fédérale de Lausanne（洛桑联邦理工学院）；Shenzhen University（深圳大学）；Peng Cheng Laboratory（鹏城实验室）
3D Smoke Scene Reconstruction Guided by Vision Priors from Multimodal Large Language Models
Hefei University of Technology（合肥工业大学）；Institute of Artificial Intelligence, Hefei Comprehensive National Science Center（合肥综合性国家科学中心人工智能研究院）；Anhui University（安徽大学）；United Arab Emirates University（阿联酋大学）；Nanyang Technological University（南洋理工大学）
DEAL: Data-Efficient Adversarial Learning for High-Quality Infrared Imaging
School of Software Technology, Dalian University of Technology（大连理工大学软件学院）；School of Mechanical Engineering, Dalian University of Technology（大连理工大学机械工程学院）
UIEDP:Underwater Image Enhancement with Diffusion Prior
Beihang University（北京航空航天大学）；Hangzhou Innovation Institute, Beihang University（北京航空航天大学杭州创新研究院）；University of Chinese Academy of Sciences（中国科学院大学）；Tsinghua University（清华大学）
EEG2Vision: A Multimodal EEG-Based Framework for 2D Visual Reconstruction in Cognitive Neuroscience
Università Politecnica delle Marche（马尔凯理工大学）；University of Macerata（马切拉塔大学）；Horizon Intelligence Labs（地平线智能实验室）；Harvard Medical School（哈佛医学院）；Massachusetts General Hospital（麻省总医院）
Training-Free Large Model Priors for Multiple-in-One Image Restoration
Hefei Institutes of Physical Science, Chinese Academy of Sciences（中国科学院合肥物质科学研究院）；University of Science and Technology of China（中国科学技术大学）；Xiamen University（厦门大学）
From Pixels to Places: A Systematic Benchmark for Evaluating Image Geolocalization Ability in Large Language Models
University of South Florida Tampa USA；University of Alabama Tuscaloosa USA；University of Michigan Ann Arbor USA；Texas Tech University Lubbock USA；Texas A \& M University College Station USA；University of Pittsburgh Pittsburgh USA；University of South Florida；University of Alabama；University of Michigan；Texas Tech University；Texas A \& M University；University of Pittsburgh
