Tootfinder

Diffusion Once and Done: Degradation-Aware LoRA for Efficient All-in-One Image Restoration
Ni Tang, Xiaotong Luo, Zihan Cheng, Liangtai Zhou, Dongxiao Zhang, Yanyun Qu
https://arxiv.org/abs/2508.03373 …

Diffusion Once and Done: Degradation-Aware LoRA for Efficient All-in-One Image Restoration
Diffusion models have revealed powerful potential in all-in-one image restoration (AiOIR), which is talented in generating abundant texture details. The existing AiOIR methods either retrain a diffusion model or fine-tune the pretrained diffusion model with extra conditional guidance. However, they often suffer from high inference costs and limited adaptability to diverse degradation types. In this paper, we propose an efficient AiOIR method, Diffusion Once and Done (DOD), which aims to achieve…

Large Language Model-Driven Closed-Loop UAV Operation with Semantic Observations
Wenhao Wang, Yanyan Li, Long Jiao, Jiawei Yuan
https://arxiv.org/abs/2507.01930

Large Language Model-Driven Closed-Loop UAV Operation with Semantic Observations
Large Language Models (LLMs) have revolutionized robotic autonomy, including Unmanned Aerial Vehicles (UAVs). Recent studies have demonstrated the potential of LLMs for translating human instructions into executable control code for UAV operations. However, LLMs still face challenges from logical reasoning and complex decision-making, leading to concerns about the reliability of LLM-driven UAV operations. In this paper, we propose a LLM-driven closed-loop control framework that enables reliable…

Integrated photonic neuromorphic computing: device, architecture, chip, algorithm
Shuiying Xiang, Chengyang Yu, Yizhi Wang, Xintao Zeng, Yuna Zhang, Dianzhuang Zheng, Xinran Niu, Haowen Zhao, Hanxu Zhou, Yanan Han, Xingxing Guo, Yahui Zhang, Yue Hao
https://arxiv.org/abs/2509.01262

Integrated photonic neuromorphic computing: device, architecture, chip, algorithm
Artificial intelligence (AI) has experienced explosive growth in recent years. The large models have been widely applied in various fields, including natural language processing, image generation, and complex decision-making systems, revolutionizing technological paradigms across multiple industries. Nevertheless, the substantial data processing demands during model training and inference result in the computing power bottleneck. Traditional electronic chips based on the von Neumann architectur…

From Revolution to Ruin: An Empirical Analysis Yemen's State Collapse
Riste Ichev, Rok Spruk
https://arxiv.org/abs/2507.08512 https://

From Revolution to Ruin: An Empirical Analysis Yemen's State Collapse
We assess the broad repercussions of Yemen's 2011 revolution and subsequent civil war on its macroeconomic trajectories, human development, and quality of governance by constructing counterfactual benchmarks using a balanced panel of 37 developing countries over 1990-2022. Drawing on matrix-completion estimators with alternative shrinkage regimes and a LASSO-augmented synthetic-control method, we generate Yemen's hypothetical no-conflict paths for key macroeconomic aggregates, demographic and h…

Movable-Antenna Empowered AAV-Enabled Data Collection over Low-Altitude Wireless Networks
Xuhui Zhang, Wenchao Liu, Jinke Ren, Chunjie Wang, Huijun Xing, Yanyan Shen, Shuguang Cui
https://arxiv.org/abs/2507.15515

Movable-Antenna Empowered AAV-Enabled Data Collection over Low-Altitude Wireless Networks
Movable-antennas (MAs) are revolutionizing spatial signal processing by providing flexible beamforming in next-generation wireless systems. This paper investigates an MA-empowered autonomous aerial vehicle (AAV) system in low-altitude wireless networks (LAWNs) for uplink data collection from ground users. We aim to maximize the sum achievable rate by jointly optimizing the AAV trajectory, receive beamforming, and MA positions. An efficient alternating optimization (AO) algorithm that incorporat…

Photocatalytic CO2 Reduction Enhanced by Synergetic Interactions among Photon Phonon and Molecule
Chen Sun, Yimin Xuan
https://arxiv.org/abs/2508.12262 https://

Photocatalytic CO2 Reduction Enhanced by Synergetic Interactions among Photon Phonon and Molecule
Photocatalytic CO2 reduction is limited by inefficient CO2 activation and poor solar spectrum utilization. Here, we discovered and revealed the vibration coupling mechanism among photons, phonons, and molecules, which remarkably enhances photocatalytic catalysis of CO2 into fuels. We designed the nitrogen-doped Cu2O-based catalyst loaded onto the quartz optical substrate. The N-doping Cu2O converts linearly geometry of adsorbed CO2 molecules, which efficiently lowers the activation barrier and …

Bipedal Balance Control with Whole-body Musculoskeletal Standing and Falling Simulations
Chengtian Ma, Yunyue Wei, Chenhui Zuo, Chen Zhang, Yanan Sui
https://arxiv.org/abs/2506.09383

Bipedal Balance Control with Whole-body Musculoskeletal Standing and Falling Simulations
Balance control is important for human and bipedal robotic systems. While dynamic balance during locomotion has received considerable attention, quantitative understanding of static balance and falling remains limited. This work presents a hierarchical control pipeline for simulating human balance via a comprehensive whole-body musculoskeletal system. We identified spatiotemporal dynamics of balancing during stable standing, revealed the impact of muscle injury on balancing behavior, and genera…