Real Time
Real-time processing focuses on developing systems capable of analyzing and responding to data instantaneously, crucial for applications demanding immediate feedback. Current research emphasizes efficient algorithms and model architectures, such as those based on deep learning, to reduce computational latency in diverse domains including robotics, healthcare, and AI-assisted tutoring. This field's advancements are driving progress in areas like autonomous navigation, personalized healthcare monitoring, and human-computer interaction, enabling more responsive and effective systems.
Papers
Safe Guard: an LLM-agent for Real-time Voice-based Hate Speech Detection in Social Virtual Reality
Yiwen Xu, Qinyang Hou, Hongyu Wan, Mirjana Prpa
SEAL: Suite for Evaluating API-use of LLMs
Woojeong Kim, Ashish Jagmohan, Aditya Vempaty
TextToon: Real-Time Text Toonify Head Avatar from Single Video
Luchuan Song, Lele Chen, Celong Liu, Pinxin Liu, Chenliang Xu
Bilevel Optimization for Real-Time Control with Application to Locomotion Gait Generation
Zachary Olkin, Aaron D. Ames
Hierarchical LLMs In-the-loop Optimization for Real-time Multi-Robot Target Tracking under Unknown Hazards
Yuwei Wu, Yuezhan Tao, Peihan Li, Guangyao Shi, Gaurav S. Sukhatmem, Vijay Kumar, Lifeng Zhou
Enabling Real-Time Conversations with Minimal Training Costs
Wang Xu, Shuo Wang, Weilin Zhao, Xu Han, Yukun Yan, Yudi Zhang, Zhe Tao, Zhiyuan Liu, Wanxiang Che
Safe and Real-Time Consistent Planning for Autonomous Vehicles in Partially Observed Environments via Parallel Consensus Optimization
Lei Zheng, Rui Yang, Minzhe Zheng, Michael Yu Wang, Jun Ma
Real-time Coupled Centroidal Motion and Footstep Planning for Biped Robots
Tara Bartlett, Ian R. Manchester
Towards Real-Time Generation of Delay-Compensated Video Feeds for Outdoor Mobile Robot Teleoperation
Neeloy Chakraborty, Yixiao Fang, Andre Schreiber, Tianchen Ji, Zhe Huang, Aganze Mihigo, Cassidy Wall, Abdulrahman Almana, Katherine Driggs-Campbell