Papers by Aljoscha Burchardt
Clinical Text Anonymization, its Influence on Downstream NLP Tasks and the Risk of Re-Identification (2023.eacl-srw)
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| Challenge: | De-identification and anonymization of clinical data is needed to solve access to clinicaldata. |
| Approach: | They propose to use text anonymization techniques to break the anonymization of clinical data . they propose to apply a re-identification attack to the anonymized text data to break this. |
| Outcome: | The proposed approach can break the anonymization of clinical data, the authors show . |
TQ-AutoTest – An Automated Test Suite for (Machine) Translation Quality (L18-1)
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| Challenge: | Especially the trend towards neural MT has renewed peoples' interest in better and more analytical diagnostic methods for MT quality. |
| Approach: | They propose a framework that supports a linguistic evaluation of machine translations using test suites. |
| Outcome: | The proposed framework supports linguistic evaluation of (machine) translations using test suites. |
Large Language Models Are Echo Chambers (2024.lrec-main)
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Jan Nehring, Aleksandra Gabryszak, Pascal Jürgens, Aljoscha Burchardt, Stefan Schaffer, Matthias Spielkamp, Birgit Stark
| Challenge: | Modern large language models and chatbots are subject to criticism in many aspects. |
| Approach: | They show that large language models and chatbots are echo chambers . they annotate inputs and show that all chatbot agree . |
| Outcome: | The proposed models show that they tend to agree with the opinions of their users. |
An Annotated Corpus of Textual Explanations for Clinical Decision Support (2022.lrec-1)
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Roland Roller, Aljoscha Burchardt, Nils Feldhus, Laura Seiffe, Klemens Budde, Simon Ronicke, Bilgin Osmanodja
| Challenge: | In recent years, machine learning for clinical decision support has gained more and more attention. |
| Approach: | They propose to use XAI to provide an explanation of a model's decision making process by constructing a corpus of sentences that are annotated with different semantic layers. |
| Outcome: | The proposed models outperform physicians on very specific, narrow tasks or can help physicians to work more efficiently. |
A Linguistically Motivated Test Suite to Semi-Automatically Evaluate German–English Machine Translation Output (2022.lrec-1)
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Vivien Macketanz, Eleftherios Avramidis, Aljoscha Burchardt, He Wang, Renlong Ai, Shushen Manakhimova, Ursula Strohriegel, Sebastian Möller, Hans Uszkoreit
| Challenge: | Using fine-grained evaluation techniques, translation outputs have become better and more fluent. |
| Approach: | They propose a fine-grained test suite for the language pair German–English . they describe the creation and implementation of the test suite in detail . |
| Outcome: | The proposed test suite is based on linguistically motivated categories and phenomena and semi-automatic evaluation is carried out with regular expressions. |