System Description
System descriptions encompass the design, implementation, and evaluation of computational systems addressing diverse challenges. Current research focuses on improving system efficiency and accuracy through techniques like hybrid neural networks for optimal control, fine-tuned BERT models for question answering, and various large language model (LLM) applications for tasks ranging from automatic scoring to creative idea generation. These advancements are significant for improving automation in various fields, from energy management and disaster response to healthcare and education, and for advancing our understanding of AI capabilities and limitations.
Papers
Edge Video Analytics: A Survey on Applications, Systems and Enabling Techniques
Renjie Xu, Saiedeh Razavi, Rong Zheng
SongRewriter: A Chinese Song Rewriting System with Controllable Content and Rhyme Scheme
Yusen Sun, Liangyou Li, Qun Liu, Dit-Yan Yeung
BJTU-WeChat's Systems for the WMT22 Chat Translation Task
Yunlong Liang, Fandong Meng, Jinan Xu, Yufeng Chen, Jie Zhou
Betting the system: Using lineups to predict football scores
George Peters, Diogo Pacheco
THUEE system description for NIST 2020 SRE CTS challenge
Yu Zheng, Jinghan Peng, Miao Zhao, Yufeng Ma, Min Liu, Xinyue Ma, Tianyu Liang, Tianlong Kong, Liang He, Minqiang Xu
System theoretic approach of information processing in nested cellular automata
Jerzy Szynka