Zobrazeno 1 - 10
of 2 263 276
pro vyhledávání: '"P. Then"'
Ubiquitous mobile devices have catalyzed the development of vehicle crowd sensing (VCS). In particular, vehicle sensing systems show great potential in the flexible acquisition of spatio-temporal urban data through built-in sensors under diverse sens
Externí odkaz:
http://arxiv.org/abs/2411.18432
Autor:
Pan, Shijie, Cheng, Aoran, Sun, Yiqi, Kang, Kai, Pais, Cristobal, Zhou, Yulun, Shen, Zuo-Jun Max
Drone swarms coupled with data intelligence can be the future of wildfire fighting. However, drone swarm firefighting faces enormous challenges, such as the highly complex environmental conditions in wildfire scenes, the highly dynamic nature of wild
Externí odkaz:
http://arxiv.org/abs/2411.16144
The predict-then-optimize (PTO) framework is indispensable for addressing practical stochastic decision-making tasks. It consists of two crucial steps: initially predicting unknown parameters of an optimization model and subsequently solving the prob
Externí odkaz:
http://arxiv.org/abs/2411.12653
The conventional targeted adversarial attacks add a small perturbation to an image to make neural network models estimate the image as a predefined target class, even if it is not the correct target class. Recently, for visual-language models (VLMs),
Externí odkaz:
http://arxiv.org/abs/2411.00898
Group Recommendation (GR), which aims to recommend items to groups of users, has become a promising and practical direction for recommendation systems. This paper points out two issues of the state-of-the-art GR models. (1) The pre-defined and fixed
Externí odkaz:
http://arxiv.org/abs/2410.23757
The locate-then-edit paradigm has shown significant promise for knowledge editing (KE) in Large Language Models (LLMs). While previous methods perform well on single-hop fact recall tasks, they consistently struggle with multi-hop factual recall task
Externí odkaz:
http://arxiv.org/abs/2410.06331
In this work, we are interested in achieving both high text controllability and overall appearance consistency in the generation of personalized human characters. We propose a novel framework, named SerialGen, which is a serial generation method cons
Externí odkaz:
http://arxiv.org/abs/2412.01485
Autor:
Fan, Ke, Zhang, Jiangning, Yi, Ran, Gong, Jingyu, Wang, Yabiao, Wang, Yating, Tan, Xin, Wang, Chengjie, Ma, Lizhuang
Text-to-motion generation is a crucial task in computer vision, which generates the target 3D motion by the given text. The existing annotated datasets are limited in scale, resulting in most existing methods overfitting to the small datasets and una
Externí odkaz:
http://arxiv.org/abs/2411.04079
Autor:
Temizöz, Tarkan, Imdahl, Christina, Dijkman, Remco, Lamghari-Idrissi, Douniel, van Jaarsveld, Willem
Deploying deep reinforcement learning (DRL) in real-world inventory management presents challenges, including dynamic environments and uncertain problem parameters, e.g. demand and lead time distributions. These challenges highlight a research gap, s
Externí odkaz:
http://arxiv.org/abs/2411.00515