4 papers · 1 filter
Reverse Engineering Human Preferences with Reinforcement Learning
Lisa Alazraki, Tan Yi-Chern, Jon Ander Campos +3
The capabilities of Large Language Models (LLMs) are routinely evaluated by other LLMs trained to predict human preferences. This framework--known as LLM-as-a-judge--is highly scal…
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…
Atla Selene Mini: A General Purpose Evaluation Model
Andrei Alexandru, Antonia Calvi, Henry Broomfield +9
We introduce Atla Selene Mini, a state-of-the-art small language model-as-a-judge (SLMJ). Selene Mini is a general-purpose evaluator that outperforms the best SLMJs and GPT-4o-mini…
Improving Reward Models with Synthetic Critiques
Zihuiwen Ye, Fraser Greenlee-Scott, Max Bartolo +3
Reward models (RMs) play a critical role in aligning language models through the process of reinforcement learning from human feedback. RMs are trained to predict a score reflectin…