arXiv:2607. 06017v1 Announce Type: new Abstract: We study a human-AI service system in which tasks arrive sequentially and are processed through a two-stage architecture: an automated chatbot followed, when necessary, by a human agent.
By Giovanni Montanari, Marco Scarsini, Vianney Perchet
The paper proposes a multi‑modal AI framework for real‑time queue prediction, management, and resource optimisation in border control systems. It integrates heterogeneous data sources using LSTM networks for forecasting and applies Model Predictive Control and scheduling optimisation to generate actionable policies for officers. Evaluation on synthetic traffic data shows up to 35% reduction in prediction error, 30% lower average waiting time, and nearly 20% higher throughput compared to ARIMA and rule‑based methods.
By Varvara Mama, Eleni Veroni, Nikolaos Kapsalis, Christos D. Nikolopoulos, Anargyros T. Baklezos
arXiv:2607. 10694v1 Announce Type: cross Abstract: We study the problem of optimal continual fine-tuning for a pre-trained Foundation Model deployed at a resource-limited device.
By Thomas Tsouparopoulos, Iordanis Koutsopoulos
arXiv:2608. 01725v1 Announce Type: cross Abstract: Modern computing and networking infrastructure emits telemetry continuously, yet operators convert it into decisions with a separate predictor per task, entity, and horizon.
By Zifan Zhang, Zhichao Hou, Tingxiang Ji, Yuchen Liu
arXiv:2609.17193v1 Announce Type: new
Abstract: Large language model (LLM)-powered agentic AI services increasingly demand low-latency inference, motivating the deployment of LLMs across distributed...
By Zhen Li, Jun Cai, Haoran Gao, An Li, Tan Li
arXiv:2505. 21331v2 Announce Type: replace-cross Abstract: In content moderation for social media platforms, the cost of delaying the review of a content is proportional to its view trajectory, which fluctuates and is apriori unknown.
By Caner Gocmen, Thodoris Lykouris, Deeksha Sinha, Wentao Weng