4 papers
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…
How Does Quantization Affect Multilingual LLMs?
Kelly Marchisio, Saurabh Dash, Hongyu Chen +4
Quantization techniques are widely used to improve inference speed and deployment of large language models. While a wide body of work examines the impact of quantization on LLMs in…
TICKing All the Boxes: Generated Checklists Improve LLM Evaluation and Generation
Jonathan Cook, Tim Rocktäschel, Jakob Foerster +2
Given the widespread adoption and usage of Large Language Models (LLMs), it is crucial to have flexible and interpretable evaluations of their instruction-following ability. Prefer…
On Leakage of Code Generation Evaluation Datasets
Alexandre Matton, Tom Sherborne, Dennis Aumiller +7
In this paper, we consider contamination by code generation test sets, in particular in their use in modern large language models. We discuss three possible sources of such contami…