10 accepted papers
With Large Language Models (LLMs) becoming increasingly multilingual, effective knowledge editing (KE) needs to propagate edits across languages. Evaluation of the existing methods for cross-lingual knowledge editing (CKE) is limited both w.r.t. edit effectiveness: benchmarks do not account for enti…
The construct of morality permeates our entire lives and influences our behavior and how we perceive others. It therefore comes at no surprise that morality also plays an important role in politics, as morally framed arguments are perceived as more appealing and persuasive. Thus, being able to ident
In this paper, we study the surprising impact that truncating text embeddings has on downstream performance. We consistently observe across 6 state-of-the-art text encoders and 26 downstream tasks, that randomly removing up to 50% of embedding dimensions results in only a minor drop in performance,
Large language models (LLMs) are able to generate grammatically well-formed text, but how do they encode their syntactic knowledge internally? While prior work has focused largely on binary grammatical contrasts, in this work, we study the representation and control of two multidimensional hierarchi
Creating high-quality scientific figures can be time-consuming and challenging, even though sketching ideas on paper is relatively easy. Furthermore, recreating existing figures that are not stored in formats preserving semantic information is equally complex. To tackle this problem, we introduce De…
This paper presents a new perspective on framing through the lens of speech acts and investigates how politicians make use of different pragmatic speech act functions in political debates. To that end, we created a new resource of German parliamentary debates, annotated with fine-grained speech act…
This paper presents GePaDe_SpkAtt , a new corpus for speaker attribution in German parliamentary debates, with more than 7,700 manually annotated events of speech, thought and writing. Our role inventory includes the sources, addressees, messages and topics of the speech event and also two additiona…
While pretrained language models (PLMs) primarily serve as general-purpose text encoders that can be fine-tuned for a wide variety of downstream tasks, recent work has shown that they can also be rewired to produce high-quality word representations (i.e., static word embeddings) and yield good perfo…
Cross-lingual transfer learning from high-resource to medium and low-resource languages has shown encouraging results. However, the scarcity of resources in target languages remains a challenge. In this work, we resort to data augmentation and continual pre-training for domain adaptation to improve…
In this paper, we introduce the task of political coalition signal prediction from text, that is, the task of recognizing from the news coverage leading up to an election the (un)willingness of political parties to form a government coalition. We decompose our problem into two related, but distinct…