Tootfinder

Rethinking User Empowerment in AI Recommender Systems: Designing through Transparency and Control
Mengke Wu, Weizi Liu, Yanyun Wang, Weiyu Ding, Mike Yao
https://arxiv.org/abs/2509.11098

Rethinking User Empowerment in AI Recommender Systems: Designing through Transparency and Control
Smart recommendation algorithms have revolutionized content delivery and improved efficiency across various domains. However, concerns about user agency persist due to their inherent opacity (information asymmetry) and one-way influence (power asymmetry). This study introduces a provotype designed to enhance user agency by providing actionable transparency and control over data management and content delivery. We conducted qualitative interviews with 19 participants to explore their preferences…

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 …

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…

PolyLink: A Blockchain Based Decentralized Edge AI Platform for LLM Inference
Hongbo Liu, Jiannong Cao, Bo Yang, Dongbin Bai, Yinfeng Cao, Xiaoming Shen, Yinan Zhang, Jinwen Liang, Shan Jiang, Mingjin Zhang
https://arxiv.org/abs/2510.02395

PolyLink: A Blockchain Based Decentralized Edge AI Platform for LLM Inference
The rapid advancement of large language models (LLMs) in recent years has revolutionized the AI landscape. However, the deployment model and usage of LLM services remain highly centralized, creating significant trust issues and costs for end users and developers. To address these issues, we propose PolyLink, a blockchain-based decentralized AI platform that decentralizes LLM development and inference. Specifically, PolyLink introduces a decentralized crowdsourcing architecture that supports sin…

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…