4 papers
Tackling the Low-resource Challenge for Canonical Segmentation
Manuel Mager, Özlem Çetinoğlu, Katharina Kann
Canonical morphological segmentation consists of dividing words into their standardized morphemes. Here, we are interested in approaches for the task when training data is limited.…
GPT-too: A language-model-first approach for AMR-to-text generation
Manuel Mager, Ramon Fernandez Astudillo, Tahira Naseem +4
Meaning Representations (AMRs) are broad-coverage sentence-level semantic graphs. Existing approaches to generating text from AMR have focused on training sequence-to-sequence or g…
The IMS-CUBoulder System for the SIGMORPHON 2020 Shared Task on Unsupervised Morphological Paradigm Completion
Manuel Mager, Katharina Kann
In this paper, we present the systems of the University of Stuttgart IMS and the University of Colorado Boulder (IMS-CUBoulder) for SIGMORPHON 2020 Task 2 on unsupervised morpholog…
Subword-Level Language Identification for Intra-Word Code-Switching
Manuel Mager, Özlem Çetinoğlu, Katharina Kann
Language identification for code-switching (CS), the phenomenon of alternating between two or more languages in conversations, has traditionally been approached under the assumptio…