Analyzing the Impact of Participant Failures in Cross-Silo Federated Learning
arXiv:2511.14456v1 Announce Type: cross Abstract: Federated learning (FL) is a new paradigm for training machine learning (ML) models without sharing…
arXiv:2511.14456v1 Announce Type: cross Abstract: Federated learning (FL) is a new paradigm for training machine learning (ML) models without sharing…
arXiv:2511.14461v1 Announce Type: cross Abstract: Using multiple carousels, lists that wrap around and can be scrolled, is the basis for…
arXiv:2511.13625v2 Announce Type: replace-cross Abstract: Bayesian optimization (BO) efficiently finds high-performing parameters by maximizing an acquisition function, which models the…
arXiv:2511.13782v1 Announce Type: new Abstract: Large language models (LLMs) and vision language models (VLMs), such as DeepSeek R1,OpenAI o3, and…
arXiv:2511.10222v2 Announce Type: replace-cross Abstract: Recent progress in large language models (LLMs) has enabled understanding of both speech and non-speech…
arXiv:2511.11287v1 Announce Type: cross Abstract: The increasing deployment of autonomous AI agents on the web is hampered by a fundamental…
arXiv:2511.11298v1 Announce Type: cross Abstract: Foundation models applied in robotics, particularly textbf{Vision–Language–Action (VLA)} models, hold great promise for achieving general-purpose…
arXiv:2511.10628v2 Announce Type: replace-cross Abstract: Large language models (LLMs) have demonstrated remarkable performance across a wide range of tasks, yet…
arXiv:2511.10704v1 Announce Type: new Abstract: We propose that unconstrained artificial intelligence obeys a Second Law analogous to thermodynamics, where ethical…