3 papers
cs.CL2026
Lower-Resource, Higher Scores: Language Bias in LLM Evaluators
Ej Zhou, Lucas Resck, Zheng Hui +1
LLM evaluators (trained reward models and prompted LLM-as-a-Judge) are routinely validated via pairwise accuracy. In a multilingual setting, this operates under the premise that hi…
cs.CL2026
Mitigating Cross-Lingual Cultural Inconsistencies in LLMs via Consensus-Driven Preference Optimisation
Lucas Resck, Isabelle Augenstein, Anna Korhonen
Despite their impressive capabilities, multilingual large language models (MLLMs) frequently exhibit inconsistent behaviour when the prompt's language changes. While such adaptatio…
cs.CL2024
Empirical analysis of binding precedent efficiency in Brazilian Supreme Court via case classification
Raphaël Tinarrage, Henrique Ennes, Lucas Resck +3
Binding precedents (súmulas vinculantes) constitute a juridical instrument unique to the Brazilian legal system and whose objectives include the protection of the Federal Supreme C…