• Refine your search:
  • 
    Keyword
  • 
    Creator / Publisher:
    
    • Vania, Clara (9)
    • Aji, Alham Fikri (2)
    • Bowman, Samuel R. (2)
    • Cho, Kyunghyun (2)
    • Lopez, Adam (2)
    • Louvan, Samuel (2)
    • Mahendra, Rahmad (2)
    • Rahman, Fahrurrozi (2)
    • The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021 (2)
    • ., Harsh (1)
    •   more
  • 
    Year
  • 
    Medium
  • 
    Type
  • 
    BLLDB-Access:
    • free (9)
    • subject to license (0)

Search in the Catalogues and Directories

All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 9 of 9 1 IndoNLI: A Natural Language Inference Dataset for Indonesian ... Mahendra, Rahmad; Aji, Alham Fikri; Louvan, Samuel. - : arXiv, 2021 BASE Show details 2 IndoNLI: A Natural Language Inference Dataset for Indonesian ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Aji, Alham Fikri; Louvan, Samuel. - : Underline Science Inc., 2021 BASE Show details 3 What Ingredients Make for an Effective Crowdsourcing Protocol for Difficult NLU Data Collection Tasks? ... The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021; ., Harsh; Bowman, Samuel R.. - : Underline Science Inc., 2021 BASE Show details 4 Comparing Test Sets with Item Response Theory ... The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021; Bowman, Samuel R.; Cho, Kyunghyun. - : Underline Science Inc., 2021 BASE Show details 5 VisualSem: A High-quality Knowledge Graph for Vision and Language ... Alberts, Houda; Huang, Teresa; Deshpande, Yash. - : arXiv, 2020 BASE Show details 6 On understanding character-level models for representing morphology ... Vania, Clara. - : The University of Edinburgh, 2020 BASE Show details 7 On understanding character-level models for representing morphology Vania, Clara. - : The University of Edinburgh, 2020 Abstract: Morphology is the study of how words are composed of smaller units of meaning (morphemes). It allows humans to create, memorize, and understand words in their language. To process and understand human languages, we expect our computational models to also learn morphology. Recent advances in neural network models provide us with models that compose word representations from smaller units like word segments, character n-grams, or characters. These so-called subword unit models do not explicitly model morphology yet they achieve impressive performance across many multilingual NLP tasks, especially on languages with complex morphological processes. This thesis aims to shed light on the following questions: (1) What do subword unit models learn about morphology? (2) Do we still need prior knowledge about morphology? (3) How do subword unit models interact with morphological typology? First, we systematically compare various subword unit models and study their performance across language typologies. We show that models based on characters are particularly effective because they learn orthographic regularities which are consistent with morphology. To understand which aspects of morphology are not captured by these models, we compare them with an oracle with access to explicit morphological analysis. We show that in the case of dependency parsing, character-level models are still poor in representing words with ambiguous analyses. We then demonstrate how explicit modeling of morphology is helpful in such cases. Finally, we study how character-level models perform in low resource, cross-lingual NLP scenarios, whether they can facilitate cross-linguistic transfer of morphology across related languages. While we show that cross-lingual character-level models can improve low-resource NLP performance, our analysis suggests that it is mostly because of the structural similarities between languages and we do not yet find any strong evidence of crosslinguistic transfer of morphology. This thesis presents a careful, in-depth study and analyses of character-level models and their relation to morphology, providing insights and future research directions on building morphologically-aware computational NLP models. Keyword: character-level models; dependency parsing; morphemes; morphology; natural language processing; NLP URL: https://doi.org/10.7488/era/49 https://hdl.handle.net/1842/36742 BASE Hide details 8 LINSPECTOR: Multilingual Probing Tasks for Word Representations Şahin, Gözde Gül; Vania, Clara; Kuznetsov, Ilia... In: Computational Linguistics, Vol 46, Iss 2, Pp 335-385 (2020) (2020) BASE Show details 9 CoNLL 2017 Shared Task System Outputs Zeman, Daniel; Potthast, Martin; Straka, Milan. - : Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL), 2017 BASE Show details

Mobile view All Catalogues UB Frankfurt Linguistik 0 IDS Mannheim 0 OLC Linguistik 0 UB Frankfurt Retrokatalog 0 DNB Subject Category Language 0 Institut für Empirische Sprachwissenschaft 0 Leibniz-Centre General Linguistics (ZAS) 0 Bibliographies BLLDB 0 BDSL 0 IDS Bibliografie zur deutschen Grammatik 0 IDS Bibliografie zur Gesprächsforschung 0 IDS Konnektoren im Deutschen 0 IDS Präpositionen im Deutschen 0 IDS OBELEX meta 0 MPI-SHH Linguistics Collection 0 MPI for Psycholinguistics 0 Linked Open Data catalogues Annohub 0 Online resources Link directory 0 Journal directory 0 Database directory 0 Dictionary directory 0 Open access documents BASE 9 Linguistik-Repository 0 IDS Publikationsserver 0 Online dissertations 0 Language Description Heritage 0