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The Role of Explainability in Collaborative Human-AI Disinformation Detection
Manual verification has become very challenging based on the increasing volume of information shared online and the role of generative …
Vera Schmitt
,
Luis Felipe Villa-Arenas
,
Nils Feldhus
,
Joachim Meyer
,
Robert P. Spang
,
Sebastian Möller
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DOI
LLMCheckup: Conversational Examination of Large Language Models via Interpretability Tools and Self-Explanations
Interpretability tools that offer explanations in the form of a dialogue have demonstrated their efficacy in enhancing users’ …
Qianli Wang
,
Tatiana Anikina
,
Nils Feldhus
,
Josef Van Genabith
,
Leonhard Hennig
,
Sebastian Möller
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Retrieval-Augmented Knowledge Integration into Language Models: A Survey
Yuxuan Chen
,
Daniel Röder
,
Justus-Jonas Erker
,
Leonhard Hennig
,
Philippe Thomas
,
Sebastian Möller
,
Roland Roller
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A Dataset for Pharmacovigilance in German, French, and Japanese: Annotating Adverse Drug Reactions across Languages
User-generated data sources have gained significance in uncovering Adverse Drug Reactions (ADRs), with an increasing number of …
Lisa Raithel
,
Hui-Syuan Yeh
,
Shuntaro Yada
,
Cyril Grouin
,
Thomas Lavergne
,
Aurélie Névéol
,
Patrick Paroubek
,
Philippe Thomas
,
Tomohiro Nishiyama
,
Sebastian Möller
,
Eiji Aramaki
,
Yuji Matsumoto
,
Roland Roller
,
Pierre Zweigenbaum
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Large Language Models Are Echo Chambers
Modern large language models and chatbots based on them show impressive results in text generation and dialog tasks. At the same time, …
Jan Nehring
,
Aleksandra Gabryszak
,
Pascal Jürgens
,
Aljoscha Burchardt
,
Stefan Schaffer
,
Matthias Spielkamp
,
Birgit Stark
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Assessing Authenticity and Anonymity of Synthetic User-generated Content in the Medical Domain
Since medical text cannot be shared easily due to privacy concerns, synthetic data bears much potential for natural language processing …
Tomohiro Nishiyama
,
Lisa Raithel
,
Roland Roller
,
Pierre Zweigenbaum
,
Eiji Aramaki
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Automatic User Experience Evaluation of Goal-Oriented Dialogs Using Pre- Trained Language Models
Dialog evaluation methods based on Pre-trained Language Models (Pr-LMs) have been primarily used for open-domain dialogs with the goal …
Mika Rebensburg
,
Stefan Hillmann
,
Nils Feldhus
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InterroLang: Exploring NLP Models and Datasets through Dialogue-based Explanations
While recently developed NLP explainability methods let us open the black box in various ways (Madsen et al., 2022), a missing …
Nils Feldhus
,
Qianli Wang
,
Tatiana Anikina
,
Sahil Chopra
,
Cennet Oguz
,
Sebastian Möller
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DOI
Factuality Detection using Machine Translation - a Use Case for German Clinical Text
Factuality can play an important role when automatically processing clinical text, as it makes a difference if particular symptoms are …
Mohammed Bin Sumait
,
Aleksandra Gabryszak
,
Leonhard Hennig
,
Roland Roller
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Project
Inseq: An Interpretability Toolkit for Sequence Generation Models
Past work in natural language processing interpretability focused mainly on popular classification tasks while largely overlooking …
Gabriele Sarti
,
Nils Feldhus
,
Ludwig Sickert
,
Oskar Van Der Wal
,
Malvina Nissim
,
Arianna Bisazza
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