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pro vyhledávání: '"Ke, Fucai"'
Autor:
Ke, Fucai, Cai, Zhixi, Jahangard, Simindokht, Wang, Weiqing, Haghighi, Pari Delir, Rezatofighi, Hamid
Recent advances in visual reasoning (VR), particularly with the aid of Large Vision-Language Models (VLMs), show promise but require access to large-scale datasets and face challenges such as high computational costs and limited generalization capabi
Externí odkaz:
http://arxiv.org/abs/2403.12884
Predicting electric vehicle (EV) charging events is crucial for load scheduling and energy management, promoting seamless transportation electrification and decarbonization. While prior studies have focused on EV charging demand prediction, primarily
Externí odkaz:
http://arxiv.org/abs/2403.13246
Graph Enhanced Reinforcement Learning for Effective Group Formation in Collaborative Problem Solving
This study addresses the challenge of forming effective groups in collaborative problem-solving environments. Recognizing the complexity of human interactions and the necessity for efficient collaboration, we propose a novel approach leveraging graph
Externí odkaz:
http://arxiv.org/abs/2403.10006
Understanding electric vehicle (EV) charging on the distribution network is key to effective EV charging management and aiding decarbonization across the energy and transport sectors. Advanced metering infrastructure has allowed distribution system o
Externí odkaz:
http://arxiv.org/abs/2312.01887
Knowledge tracing (KT) aims to leverage students' learning histories to estimate their mastery levels on a set of pre-defined skills, based on which the corresponding future performance can be accurately predicted. As an important way of providing pe
Externí odkaz:
http://arxiv.org/abs/2212.12139
Publikováno v:
In Knowledge-Based Systems 25 January 2024 284
