34 citations · 41 across the 5 of their papers we have counts for
9 papers
From Zero to Hero: On the Limitations of Zero-Shot Cross-Lingual Transfer with Multilingual Transformers
Anne Lauscher, Vinit Ravishankar, Ivan Vulić +1
Massively multilingual transformers pretrained with language modeling objectives (e.g., mBERT, XLM-R) have become a de facto default transfer paradigm for zero-shot cross-lingual t…
Towards Instance-Level Parser Selection for Cross-Lingual Transfer of Dependency Parsers
Robert Litschko, Ivan Vulić, Željko Agić +1
Current methods of cross-lingual parser transfer focus on predicting the best parser for a low-resource target language globally, that is, "at treebank level". In this work, we pro…
Windowing Models for Abstractive Summarization of Long Texts
Leon Schüller, Florian Wilhelm, Nico Kreiling +1
Neural summarization models suffer from the fixed-size input limitation: if text length surpasses the model's maximal number of input tokens, some document content (possibly summar…
Two-Level Transformer and Auxiliary Coherence Modeling for Improved Text Segmentation
Goran Glavaš, Swapna Somasundaran
Breaking down the structure of long texts into semantically coherent segments makes the texts more readable and supports downstream applications like summarization and retrieval. S…
Do We Really Need Fully Unsupervised Cross-Lingual Embeddings?
Ivan Vulić, Goran Glavaš, Roi Reichart +1
Recent efforts in cross-lingual word embedding (CLWE) learning have predominantly focused on fully unsupervised approaches that project monolingual embeddings into a shared cross-l…
A General Framework for Implicit and Explicit Debiasing of Distributional Word Vector Spaces
Anne Lauscher, Goran Glavaš, Simone Paolo Ponzetto +1
Distributional word vectors have recently been shown to encode many of the human biases, most notably gender and racial biases, and models for attenuating such biases have conseque…