activity
20242026
collaborators

8 papers

cs.CL2026

LKValues: Aligning Large Language Models with Sri Lankan Societal Values

Nethmi Muthugala, Supryadi, Surangika Ranathunga +7

Value alignment of Large Language Models (LLMs) has been shown to be culturally biased toward Western norms. This results in the mishandling of local values in multilingual societi…

cs.CL2026

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…

cs.CL2025

No Need for Explanations: LLMs can implicitly learn from mistakes in-context

Lisa Alazraki, Maximilian Mozes, Jon Ander Campos +3

Showing incorrect answers to Large Language Models (LLMs) is a popular strategy to improve their performance in reasoning-intensive tasks. It is widely assumed that, in order to be…

cs.CL2025

Colombian Waitresses y Jueces canadienses: Gender and Country Biases in Occupation Recommendations from LLMs

Elisa Forcada Rodríguez, Olatz Perez-de-Viñaspre, Jon Ander Campos +2

One of the goals of fairness research in NLP is to measure and mitigate stereotypical biases that are propagated by NLP systems. However, such work tends to focus on single axes of…

cs.CL2025

From Tools to Teammates: Evaluating LLMs in Multi-Session Coding Interactions

Nathanaël Carraz Rakotonirina, Mohammed Hamdy, Jon Ander Campos +5

Large Language Models (LLMs) are increasingly used in working environments for a wide range of tasks, excelling at solving individual problems in isolation. However, are they also…

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…