3 papers
stat.ML2026
PCS-UQ: Uncertainty Quantification via the Predictability-Computability-Stability Framework
Abhineet Agarwal, Fange Xiao, Rebecca Barter +3
As machine learning (ML) enters high-stakes domains, trustworthy uncertainty quantification (UQ) is essential for safety. In this paper we introduce PCS-UQ, a framework based on th…
cs.CL2025
Command A: An Enterprise-Ready Large Language Model
Team Cohere, :, Aakanksha +227
In this report we describe the development of Command A, a powerful large language model purpose-built to excel at real-world enterprise use cases. Command A is an agent-optimised…
cs.DC2024
A Survey on Model-heterogeneous Federated Learning: Problems, Methods, and Prospects
Boyu Fan, Siyang Jiang, Xiang Su +2
As privacy concerns continue to grow, federated learning (FL) has gained significant attention as a promising privacy-preserving technology, leading to considerable advancements in…