11 citations · 26 across the 7 of their papers we have counts for
8 papers
Multilingual Nonce Dependency Treebanks: Understanding how Language Models represent and process syntactic structure
David Arps, Laura Kallmeyer, Younes Samih +1
We introduce SPUD (Semantically Perturbed Universal Dependencies), a framework for creating nonce treebanks for the multilingual Universal Dependencies (UD) corpora. SPUD data sati…
Increasing The Performance of Cognitively Inspired Data-Efficient Language Models via Implicit Structure Building
Omar Momen, David Arps, Laura Kallmeyer
In this paper, we describe our submission to the BabyLM Challenge 2023 shared task on data-efficient language model (LM) pretraining (Warstadt et al., 2023). We train transformer-b…
DEPLAIN: A German Parallel Corpus with Intralingual Translations into Plain Language for Sentence and Document Simplification
Regina Stodden, Omar Momen, Laura Kallmeyer
Text simplification is an intralingual translation task in which documents, or sentences of a complex source text are simplified for a target audience. The success of automatic tex…
Probing for Constituency Structure in Neural Language Models
David Arps, Younes Samih, Laura Kallmeyer +1
In this paper, we investigate to which extent contextual neural language models (LMs) implicitly learn syntactic structure. More concretely, we focus on constituent structure as re…
Object-oriented lexical encoding of multiword expressions: Short and sweet
Agata Savary, Simon Petitjean, Timm Lichte +2
Multiword expressions (MWEs) exhibit both regular and idiosyncratic properties. Their idiosyncrasy requires lexical encoding in parallel with their component words. Their (at times…
Arabic Multi-Dialect Segmentation: bi-LSTM-CRF vs. SVM
Mohamed Eldesouki, Younes Samih, Ahmed Abdelali +4
Arabic word segmentation is essential for a variety of NLP applications such as machine translation and information retrieval. Segmentation entails breaking words into their consti…