3 papers
cs.CL2026
Cross-lingual Self-Consistency for Multilingual Reasoning with Language Models
Ahmed Elhady, Eneko Agirre, Mikel Artetxe
Despite expanding their multilingual coverage, the advanced reasoning capabilities of LLMs remain largely confined to a few high-resource languages like English. To address this, w…
cs.CL2025
Emergent Abilities of Large Language Models under Continued Pretraining for Language Adaptation
Ahmed Elhady, Eneko Agirre, Mikel Artetxe
Continued pretraining (CPT) is a popular approach to adapt existing large language models (LLMs) to new languages. When doing so, it is common practice to include a portion of Engl…
cs.CL2025
WiCkeD: A Simple Method to Make Multiple Choice Benchmarks More Challenging
Ahmed Elhady, Eneko Agirre, Mikel Artetxe
We introduce WiCkeD, a simple method to increase the complexity of existing multiple-choice benchmarks by randomly replacing a choice with "None of the above", a method often used…