arXiv:2606. 30650v1 Announce Type: cross Abstract: Educational support services often face a qualified-capacity problem: staff time is scarce, qualifications decay, new support needs can appear before anyone is prepared for them, and training consumes the same hours needed by current students.
By Carlos Eduardo Sanoja, Oscar Enrique Moreno Mayz
arXiv:2608. 13209v1 Announce Type: cross Abstract: Many operational decisions are sequences of interventions under a cumulative resource limit, such as a maintenance schedule within a crew-hour budget.
By Minkyoung Kim, Beakcheol Jang
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. 07157v1 Announce Type: new Abstract: Sub-model federated learning lets resource-constrained clients train width-reduced versions of a global model, but existing methods allocate capacity by device resources alone.
By Alireza Moayedikia, Alicia Troncoso Lora
arXiv:2606. 17489v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly deployed in edge-cloud inference systems to handle diverse user tasks with heterogeneous accuracy, latency, and cost profiles.
By Yin Huang, Qingsong Liu, Jie Xu
arXiv:2606. 01081v1 Announce Type: new Abstract: Decision-focused learning (DFL) trains predictive models by optimizing downstream decision quality rather than standalone prediction accuracy.
By Wyame Benslimane, Tinghan Ye, Pascal Van Hentenryck, Paul Grigas