Papers by Hannah Sterz
ReCoVeR the Target Language: Language Steering without Sacrificing Task Performance (2025.findings-emnlp)
Copied to clipboard
| Challenge: | Large Language Models exhibit more language confusion as they become multilingual . authors propose a lightweight approach for reducing language confusion based on language-specific steering vectors . |
| Approach: | They propose a lightweight approach to reduce language confusion by using language-specific steering vectors. |
| Outcome: | The proposed approach reduces language confusion in large language models . it leverages language-specific steering vectors for effective LLM steering . |
Adapters: A Unified Library for Parameter-Efficient and Modular Transfer Learning (2023.emnlp-demo)
Copied to clipboard
Clifton Poth, Hannah Sterz, Indraneil Paul, Sukannya Purkayastha, Leon Engländer, Timo Imhof, Ivan Vulić, Sebastian Ruder, Iryna Gurevych, Jonas Pfeiffer
| Challenge: | Adapters is an open-source library that unifies parameter-efficient and modular transfer learning in large language models. |
| Approach: | They propose to integrate 10 different methods into a unified interface for parameter-efficient and modular transfer learning in large language models. |
| Outcome: | The proposed library is able to perform on multiple NLP tasks and is open-source. |
M2QA: Multi-domain Multilingual Question Answering (2024.findings-emnlp)
Copied to clipboard
| Challenge: | Language varies along several axes, most importantly, language instance and domain . lack of evaluation datasets prevents transfer of NLP systems to non-dominant languages . |
| Approach: | They propose a multi-domain multilingual question answering benchmark to explore cross-lingual cross-domain performance of fine-tuned models and state-of-the-art LLMs. |
| Outcome: | The proposed benchmark compared 13,500 SQuAD 2.0-style question-answer instances in German, Turkish, and Chinese for the domains of product reviews, news, and creative writing. |
UKP-SQUARE: An Online Platform for Question Answering Research (2022.acl-demo)
Copied to clipboard
Tim Baumgärtner, Kexin Wang, Rachneet Sachdeva, Gregor Geigle, Max Eichler, Clifton Poth, Hannah Sterz, Haritz Puerto, Leonardo F. R. Ribeiro, Jonas Pfeiffer, Nils Reimers, Gözde Şahin, Iryna Gurevych
| Challenge: | Recent advances in NLP and information retrieval have given rise to a diverse set of question answering tasks that are of different formats and require different model architectures and setups. |
| Approach: | They propose an extensible online QA platform that allows users to query and analyze a large collection of modern Skills via a user-friendly web interface and integrated behavioural tests. |
| Outcome: | The proposed tool allows users to query and analyze a large collection of modern Skills via a user-friendly web interface and integrated behavioural tests. |