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In this paper we measure the step-wise latency in the pipeline of three kinds of interactive mobile video applications that are rapidly gaining popularity, namely Remote Graphics Rendering (RGR) of which we focus on mobile cloud gaming,…

Human-Computer Interaction · Computer Science 2016-11-28 Teemu Kämäräinen , Matti Siekkinen , Antti Ylä-Jääski , Wenxiao Zhang , Pan Hui

Current virtual reality systems are typically limited by performance/cost, usability (size), or a combination of both. By using a networked client/server environment, we have solved these limitations for the client. However, in doing so we…

Human-Computer Interaction · Computer Science 2019-10-11 Gregory Gutmann , Akihiko Konagaya

Real-time 3D volumetric streaming is a transformative technology that enables the seamless transmission and rendering of high-fidelity 3D models, enhancing applications in virtual reality (VR), augmented reality (AR), gaming, telepresence,…

Networking and Internet Architecture · Computer Science 2026-05-27 Seungwoo Hong , Hosun Yoon , Seong Moon , Inayat Ali

Supporting real-time interactions between human controllers and remote devices remains a challenging goal in the Metaverse due to the stringent requirements on computing workload, communication throughput, and round-trip latency. In this…

Robotics · Computer Science 2024-07-24 Kan Chen , Zhen Meng , Xiangmin Xu , Changyang She , Philip G. Zhao

The transformation towards intelligence in various industries is creating more demand for intelligent and flexible products. In the field of robotics, learning-based methods are increasingly being applied, with the purpose of training…

Robotics · Computer Science 2022-09-09 Xinjie Liu

Classically, rasterization techniques are performed for real-time rendering to meet the constraint of interactive frame rates. However, such techniques do not produce realistic results as compared to ray tracing approaches. Hence, hybrid…

Graphics · Computer Science 2022-10-31 Yu Wei Tan , Alden Tan , Nicholas Nge , Anand Bhojan

Interactive Imitation Learning (IIL) is a branch of Imitation Learning (IL) where human feedback is provided intermittently during robot execution allowing an online improvement of the robot's behavior. In recent years, IIL has increasingly…

Reinforcement Learning (RL) in various decision-making tasks of machine learning provides effective results with an agent learning from a stand-alone reward function. However, it presents unique challenges with large amounts of environment…

Machine Learning · Computer Science 2020-03-10 Neda Navidi

State-of-the-art digital circuit design tools almost exclusively rely on pure and inertial delay for timing simulations. While these provide reasonable estimations at very low execution time in the average case, their ability to cover…

Other Computer Science · Computer Science 2021-07-20 Jürgen Maier

This paper introduces IRIS, an Immersive Robot Interaction System leveraging Extended Reality (XR). Existing XR-based systems enable efficient data collection but are often challenging to reproduce and reuse due to their specificity to…

Action-conditioned video prediction models (often referred to as world models) have shown strong potential for robotics applications, but existing approaches are often slow and struggle to capture physically consistent interactions over…

With the rapid evolution of wireless mobile devices, there emerges an increased need to design effective collaboration mechanisms between intelligent agents, so as to gradually approach the final collective objective through continuously…

Artificial Intelligence · Computer Science 2021-02-02 Xing Xu , Rongpeng Li , Zhifeng Zhao , Honggang Zhang

We investigated the challenges of mitigating response delays in free-form conversations with virtual agents powered by Large Language Models (LLMs) within Virtual Reality (VR). For this, we used conversational fillers, such as gestures and…

Real-Time Networks (RTNs) provide latency guarantees for time-critical applications and it aims to support different traffic categories via various scheduling mechanisms. Those scheduling mechanisms rely on a precise network performance…

Networking and Internet Architecture · Computer Science 2021-04-07 Chien-Cheng Wu

Robot learning methods have recently made great strides, but generalization and robustness challenges still hinder their widespread deployment. Failing to detect and address potential failures renders state-of-the-art learning systems not…

Robotics · Computer Science 2024-03-11 Huihan Liu , Shivin Dass , Roberto Martín-Martín , Yuke Zhu

Deep research agents powered by Large Language Models (LLMs) can perform multi-step reasoning, web exploration, and long-form report generation. However, most existing systems operate in an autonomous manner, assuming fully specified user…

Computation and Language · Computer Science 2026-01-13 Yingchaojie Feng , Qiang Huang , Xiaoya Xie , Zhaorui Yang , Jun Yu , Wei Chen , Anthony K. H. Tung

The rapid advancement of multimodal large language models has demonstrated impressive capabilities, yet nearly all operate in an offline paradigm, hindering real-time interactivity. Addressing this gap, we introduce the Real-tIme Video…

Computer Vision and Pattern Recognition · Computer Science 2026-03-05 Yansong Shi , Qingsong Zhao , Tianxiang Jiang , Xiangyu Zeng , Yi Wang , Limin Wang

The usefulness evaluation model proposed by Cole et al. in 2009 [2] focuses on the evaluation of interactive IR systems by their support towards the user's overall goal, sub goals and tasks. This is a more human focus of the IR evaluation…

Information Retrieval · Computer Science 2018-09-10 Daniel Hienert , Peter Mutschke

LLM inference latency critically determines user experience and operational costs, directly impacting throughput under SLO constraints. Even brief latency spikes degrade service quality despite acceptable average performance. However,…

Distributed, Parallel, and Cluster Computing · Computer Science 2026-01-21 Yin Du , Jiayi Ren , Xiayu Sun , Tianyao Zhou , Haizhu Zhou , Ruiyan Ma , Danyang Zhang

Large Language Model (LLM) agents often run for many steps while re-ingesting long system instructions and large tool catalogs each turn. This increases cost, agent derailment probability, latency, and tool-selection errors. We propose…

Artificial Intelligence · Computer Science 2026-02-20 Uria Franko
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