1 citations · 1 across the 3 of their papers we have counts for
3 papers
cs.AI2025
The Multilingual Divide and Its Impact on Global AI Safety
Aidan Peppin, Julia Kreutzer, Alice Schoenauer Sebag +13
Despite advances in large language model capabilities in recent years, a large gap remains in their capabilities and safety performance for many languages beyond a relatively small…
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.CL2024★ 1 cited
RLHF Can Speak Many Languages: Unlocking Multilingual Preference Optimization for LLMs
John Dang, Arash Ahmadian, Kelly Marchisio +3
Preference optimization techniques have become a standard final stage for training state-of-art large language models (LLMs). However, despite widespread adoption, the vast majorit…