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Hannah Sterz

2 accepted papers

2025

ReCoVeR the Target Language: Language Steering without Sacrificing Task Performance

EMNLP 2025

As they become increasingly multilingual, Large Language Models (LLMs) exhibit more language confusion, i.e., they tend to generate answers in a language different from the language of the prompt or the answer language explicitly requested by the user. In this work, we propose ReCoVeR (REducing lang

2024

M2QA: Multi-domain Multilingual Question Answering

EMNLP 2024finding

Generalization and robustness to input variation are core desiderata of machine learning research. Language varies along several axes, most importantly, language instance (e.g. French) and domain (e.g. news). While adapting NLP models to new languages within a single domain, or to new domains within…